There is evidence that nonalcoholic fatty liver disease (NAFLD) is affected by gut microbiota. Therefore, we investigated its modifications in pediatric NAFLD patients using targeted metagenomics and metabolomics. Stools were collected from 61 consecutive patients diagnosed with nonalcoholic fatty liver (NAFL), nonalcoholic steatohepatitis (NASH), or obesity and 54 healthy controls (CTRLs), matched in a case‐control fashion. Operational taxonomic units were pyrosequenced targeting 16S ribosomal RNA and volatile organic compounds determined by solid‐phase microextraction gas chromatography‐mass spectrometry. The α‐diversity was highest in CTRLs, followed by obese, NASH, and NAFL patients; and β‐diversity distinguished between patients and CTRLs but not NAFL and NASH. Compared to CTRLs, in NAFLD patients Actinobacteria were significantly increased and Bacteroidetes reduced. There were no significant differences among the NAFL, NASH, and obese groups. Overall NAFLD patients had increased levels of Bradyrhizobium, Anaerococcus, Peptoniphilus, Propionibacterium acnes, Dorea, and Ruminococcus and reduced proportions of Oscillospira and Rikenellaceae compared to CTRLs. After reducing metagenomics and metabolomics data dimensionality, multivariate analyses indicated a decrease of Oscillospira in NAFL and NASH groups and increases of Ruminococcus, Blautia, and Dorea in NASH patients compared to CTRLs. Of the 292 volatile organic compounds, 26 were up‐regulated and 2 down‐regulated in NAFLD patients. Multivariate analyses found that combination of Oscillospira, Rickenellaceae, Parabacteroides, Bacteroides fragilis, Sutterella, Lachnospiraceae, 4‐methyl‐2‐pentanone, 1‐butanol, and 2‐butanone could discriminate NAFLD patients from CTRLs. Univariate analyses found significantly lower levels of Oscillospira and higher levels of 1‐pentanol and 2‐butanone in NAFL patients compared to CTRLs. In NASH, lower levels of Oscillospira were associated with higher abundance of Dorea and Ruminococcus and higher levels of 2‐butanone and 4‐methyl‐2‐pentanone compared to CTRLs. Conclusion: 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)

Although faecal microbiota transplantation (FMT) has a well-established role in the treatment of recurrent Clostridioides difficile infection (CDI), its widespread dissemination is limited by several obstacles, including lack of dedicated centres, difficulties with donor recruitment and complexities related to regulation and safety monitoring. Given the considerable burden of CDI on global healthcare systems, FMT should be widely available to most centres. Stool banks may guarantee reliable, timely and equitable access to FMT for patients and a traceable workflow that ensures safety and quality of procedures. In this consensus project, FMT experts from Europe, North America and Australia gathered and released statements on the following issues related to the stool banking: general principles, objectives and organisation of the stool bank; selection and screening of donors; collection, preparation and storage of faeces; services and clients; registries, monitoring of outcomes and ethical issues; and the evolving role of FMT in clinical practice, Consensus on each statement was achieved through a Delphi process and then in a plenary face-to-face meeting. For each key issue, the best available evidence was assessed, with the aim of providing guidance for the development of stool banks in order to promote accessibility to FMT in clinical practice.

Compelling evidence supports the concepts that gut microbiota actively promotes weight gain and fat accumulation and sustains, indirectly, a condition of low-grade inflammation, thus enhancing the cardiovascular risk. Fewer Bacteroidetes and more Firmicutes seem to characterize the gut microbiota of obese people as compared with that of lean individuals. This difference translates into an increased efficiency of microbiota of obese individuals in harvesting energy from otherwise indigestible carbohydrates. Furthermore, the microbiota also seems able to favor fat accumulation. Indeed, studies performed in germ-free animals have demonstrated that conventionalization of sterile intestine with gut microbiota is associated with an enhanced expression of various lipogenic genes in different tissues, i.e., hepatic, adipose, and muscle tissues. Finally, the microbiota favors systemic exposure to the lipopolysaccharides (LPSs), large glycolipids derived from the outer membrane of Gram-negative bacteria. LPSs can cause a condition of “metabolic endotoxemia” characterized by low-grade inflammation, insulin resistance, and augmented cardiovascular risk. LPSs are a powerful trigger for the innate immune system response. Upon binding to the Toll-like receptor 4 and its coreceptors, LPSs trigger a cascade of responses ultimately resulting in the release of proinflammatory molecules that interfere with modulation of glucose and insulin metabolism, promote development and rupture of the atherosclerotic plaque, and favor progression of fatty liver disease to steatohepatitis. This review gives a comprehensive breakdown of the interaction among gut microbiota, LPSs, and the innate immune system in the development of obesity and promotion of an individual’s cardiovascular risk.

Fecal microbiota transplantation (FMT) is highly effective against recurrent Clostridioides difficile infection and is considered a promising treatment for other microbiome-related disorders, but a comprehensive understanding of microbial engraftment dynamics is lacking, which prevents informed applications of this therapeutic approach. Here, we performed an integrated shotgun metagenomic systematic meta-analysis of new and publicly available stool microbiomes collected from 226 triads of donors, pre-FMT recipients and post-FMT recipients across eight different disease types. By leveraging improved metagenomic strain-profiling to infer strain sharing, we found that recipients with higher donor strain engraftment were more likely to experience clinical success after FMT (P = 0.017) when evaluated across studies. Considering all cohorts, increased engraftment was noted in individuals receiving FMT from multiple routes (for example, both via capsules and colonoscopy during the same treatment) as well as in antibiotic-treated recipients with infectious diseases compared with antibiotic-naïve patients with noncommunicable diseases. Bacteroidetes and Actinobacteria species (including Bifidobacteria) displayed higher engraftment than Firmicutes except for six under-characterized Firmicutes species. Cross-dataset machine learning predicted the presence or absence of species in the post-FMT recipient at 0.77 average AUROC in leave-one-dataset-out evaluation, and highlighted the relevance of microbial abundance, prevalence and taxonomy to infer post-FMT species presence. By exploring the dynamics of microbiome engraftment after FMT and their association with clinical variables, our study uncovered species-specific engraftment patterns and presented machine learning models able to predict donors that might optimize post-FMT specific microbiome characteristics for disease-targeted FMT protocols.

The gut microbiota is composed of a huge number of different bacteria, which produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activity is affected by environmental stimuli leading to the generation of a wide number of compounds, which influence the host metabolome and human health. Indeed, metabolic profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.