Toxicological safety evaluation of pasteurizedAkkermansia muciniphila

Gut microorganisms are vital for many aspects of human health, and the commensal bacteriumAkkermansia muciniphilahas repeatedly been identified as a key component of intestinal microbiota. Reductions inA. muciniphilaabundance are associated with increased prevalence of metabolic disorders such as obesity and type 2 diabetes. It was recently discovered that administration ofA. muciniphilahas beneficial effects and that these are not diminished, but rather enhanced after pasteurization. PasteurizedA. muciniphilais proposed for use as a food ingredient, and was therefore subjected to a nonclinical safety assessment, comprising genotoxicity assays (bacterial reverse mutation and in vitro mammalian cell micronucleus tests) and a 90-day toxicity study. For the latter, Han Wistar rats were administered with the vehicle or pasteurizedA. muciniphilaat doses of 75, 375 or 1500 mg/kg body weight/day (equivalent to 4.8 x 10(9), 2.4 x 10(10), or 9.6 x 10(10)A. muciniphilacells/kg body weight/day) by oral gavage for 90 consecutive days. The study assessed potential effects on clinical observations (including detailed arena observations and a modified Irwin test), body weight, food and water consumption, clinical pathology, organ weights, and macroscopic and microscopic pathology. The results of both in vitro genotoxicity studies were negative. No test item-related adverse effects were observed in the 90-day study; therefore, 1500 mg/kg body weight/day (the highest dose tested, equivalent to 9.6 x 10(10)A. muciniphilacells/kg body weight/day) was established as the no-observed-adverse-effect-level. These results support that pasteurizedA. muciniphilais safe for use as a food ingredient.Peer reviewe

Model-driven design of a minimal medium for Akkermansia muciniphila confirms mucus adaptation

The abundance of the human intestinal symbiont Akkermansia muciniphila has found to be inversely correlated with several diseases, including metabolic syndrome and obesity. A.muciniphila is known to use mucin as sole carbon and nitrogen source. To study the physiology and the potential for therapeutic applications of this bacterium, we designed a defined minimal medium. The composition of the medium was based on the genome-scale metabolic model of A.muciniphila and the composition of mucin. Our results indicate that A.muciniphila does not code for GlmS, the enzyme that mediates the conversion of fructose-6-phosphate (Fru6P) to glucosamine-6-phosphate (GlcN6P), which is essential in peptidoglycan formation. The only annotated enzyme that could mediate this conversion is Amuc-NagB on locus Amuc_1822. We found that Amuc-NagB was unable to form GlcN6P from Fru6P at physiological conditions, while it efficiently catalyzed the reverse reaction. To overcome this inability, N-acetylglucosamine needs to be present in the medium for A.muciniphila growth. With these findings, the genome-scale metabolic model was updated and used to accurately predict growth of A.muciniphila on synthetic media. The finding that A.muciniphila has a necessity for GlcNAc, which is present in mucin further prompts the adaptation to its mucosal niche.Peer reviewe

Hepatocyte MyD88 affects bile acids, gut microbiota and metabolome contributing to regulate glucose and lipid metabolism

OBJECTIVE: To examine the role of hepatocyte myeloid differentiation primary-response gene 88 (MyD88) on glucose and lipid metabolism. DESIGN: To study the impact of the innate immune system at the level of the hepatocyte and metabolism, we generated mice harbouring hepatocyte-specific deletion of MyD88. We investigated the impact of the deletion on metabolism by feeding mice with a normal control diet or a high-fat diet for 8 weeks. We evaluated body weight, fat mass gain (using time-domain nuclear magnetic resonance), glucose metabolism and energy homeostasis (using metabolic chambers). We performed microarrays and quantitative PCRs in the liver. In addition, we investigated the gut microbiota composition, bile acid profile and both liver and plasma metabolome. We analysed the expression pattern of genes in the liver of obese humans developing non-alcoholic steatohepatitis (NASH). RESULTS: Hepatocyte-specific deletion of MyD88 predisposes to glucose intolerance, inflammation and hepatic insulin resistance independently of body weight and adiposity. These phenotypic differences were partially attributed to differences in gene expression, transcriptional factor activity (ie, peroxisome proliferator activator receptor-α, farnesoid X receptor (FXR), liver X receptors and STAT3) and bile acid profiles involved in glucose, lipid metabolism and inflammation. In addition to these alterations, the genetic deletion of MyD88 in hepatocytes changes the gut microbiota composition and their metabolomes, resembling those observed during diet-induced obesity. Finally, obese humans with NASH displayed a decreased expression of different cytochromes P450 involved in bioactive lipid synthesis. CONCLUSIONS: Our study identifies a new link between innate immunity and hepatic synthesis of bile acids and bioactive lipids. This dialogue appears to be involved in the susceptibility to alterations associated with obesity such as type 2 diabetes and NASH, both in mice and humans

The impact of human activities and lifestyles on the interlinked microbiota and health of humans and of ecosystems

Plants, animals and humans, are colonized by microorganisms (microbiota) and transiently exposed to countless others. The microbiota affects the development and function of essentially all organ systems, and contributes to adaptation and evolution, while protecting against pathogenic microorganisms and toxins. Genetics and lifestyle factors, including diet, antibiotics and other drugs, and exposure to the natural environment, affect the composition of the microbiota, which influences host health through modulation of interrelated physiological systems. These include immune system development and regulation, metabolic and endocrine pathways, brain function and epigenetic modification of the genome. Importantly, parental microbiotas have transgenerational impacts on the health of progeny. Humans, animals and plants share similar relationships with microbes. Research paradigms from humans and other mammals, amphibians, insects, planktonic crustaceans and plants demonstrate the influence of environmental microbial ecosystems on the microbiota and health of organisms, and indicate links between environmental and internal microbial diversity and good health. Therefore, overlapping compositions, and interconnected roles of microbes in human, animal and plant health should be considered within the broader context of terrestrial and aquatic microbial ecosystems that are challenged by the human lifestyle and by agricultural and industrial activities. Here, we propose research priorities and organizational, educational and administrative measures that will help to identify safe microbe-associated health-promoting modalities and practices. In the spirit of an expanding version of "One health" that includes environmental health and its relation to human cultures and habits (EcoHealth), we urge that the lifestyle-microbiota-human health nexus be taken into account in societal decision making. (C) 2018 The Authors. Published by Elsevier B.V.Peer reviewe

Microbial-host co-metabolites are prodromal markers predicting phenotypic heterogeneity in behavior, obesity, and impaired glucose tolerance

The influence of the gut microbiome on metabolic and behavioral traits is widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1 H-NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n = 50) and show that microbial-host co-metabolites are prodromal (i.e., early) markers predicting future divergence in metabolic (obesity and glucose homeostasis) and behavioral (anxiety and activity) outcomes with 94%– 100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO), a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT), and behavior while reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity

Short-term consumption of a high-fat diet increases host susceptibility to Listeria monocytogenes infection

peer-reviewedBackground A westernized diet comprising a high caloric intake from animal fats is known to influence the development of pathological inflammatory conditions. However, there has been relatively little focus upon the implications of such diets for the progression of infectious disease. Here, we investigated the influence of a high-fat (HF) diet upon parameters that influence Listeria monocytogenes infection in mice. Results We determined that short-term administration of a HF diet increases the number of goblet cells, a known binding site for the pathogen, in the gut and also induces profound changes to the microbiota and promotes a pro-inflammatory gene expression profile in the host. Host physiological changes were concordant with significantly increased susceptibility to oral L. monocytogenes infection in mice fed a HF diet relative to low fat (LF)- or chow-fed animals. Prior to Listeria infection, short-term consumption of HF diet elevated levels of Firmicutes including Coprococcus, Butyricicoccus, Turicibacter and Clostridium XIVa species. During active infection with L. monocytogenes, microbiota changes were further exaggerated but host inflammatory responses were significantly downregulated relative to Listeria-infected LF- or chow-fed groups, suggestive of a profound tempering of the host response influenced by infection in the context of a HF diet. The effects of diet were seen beyond the gut, as a HF diet also increased the sensitivity of mice to systemic infection and altered gene expression profiles in the liver. Conclusions We adopted a systems approach to identify the effects of HF diet upon L. monocytogenes infection through analysis of host responses and microbiota changes (both pre- and post-infection). Overall, the results indicate that short-term consumption of a westernized diet has the capacity to significantly alter host susceptibility to L. monocytogenes infection concomitant with changes to the host physiological landscape. The findings suggest that diet should be a consideration when developing models that reflect human infectious disease.This research was funded by the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement No. 641984, through funding of the List_MAPS consortium. We also acknowledge funding and support from Science Foundation Ireland (SFI) in the form of a center grant (APC Microbiome Ireland grant SFI/12/RC/2273)

A data integration multi-omics approach to study calorie restriction-induced changes in insulin sensitivity

Background: The mechanisms responsible for calorie restriction-induced improvement in insulin sensitivity have not been fully elucidated. Greater insight can be achieved through deep biological phenotyping of subjects undergoing calorie restriction, and integration of big data. Materials and Methods: An integrative approach was applied to investigate associations between change in insulin sensitivity and factors from host, microbiota and lifestyle after a 6-week calorie restriction period in 27 overweight or obese adults (ClinicalTrials.gov: NCT01314690). Partial least squares regression was used to determine associations of change (week 6 – baseline) between insulin sensitivity markers and lifestyle factors (diet and physical activity), subcutaneous adipose tissue (sAT) gene expression, metabolomics in serum, urine and feces, and gut microbiota composition. ScaleNet, a network learning approach based on spectral consensus strategy (SCS, developed by us) was used for reconstruction of biological networks. Results: A spectrum of variables from lifestyle factors (10 nutrients), gut microbiota (10 metagenomics species) and host multi-omics (metabolic features: 84 from serum, 73 from urine, and 131 from feces; and 257 subcutaneous adipose tissue gene probes) most associated with insulin sensitivity were identified. Biological network reconstruction using SCS, highlighted links between changes in insulin sensitivity, serum branched chain amino acids, sAT genes involved in endoplasmic reticulum stress and ubiquitination, and gut metagenomic species. Linear regression analysis to model how changes of select variables over the calorie restriction period contribute to changes in insulin sensitivity, showed greatest contributions from gut metagenomic species and fiber intake. Conclusions: This work has enhanced previous knowledge on links between host glucose homeostasis, lifestyle factors and microbiota, and has identified potential biomarkers that may be used in future studies to predict and improve individual response to weight-loss interventions. Furthermore, this is the first study showing integration of the wide range of data presented herein, identifying 115 variables of interest with respect to insulin sensitivity from the initial input, consisting of 9,986 variables

The nasal and gut microbiome in Parkinson's disease and idiopathic rapid eye movement sleep behavior disorder.

BACKGROUND: Increasing evidence connects the gut microbiota and the onset and/or phenotype of Parkinson's disease (PD). Differences in the abundances of specific bacterial taxa have been reported in PD patients. It is, however, unknown whether these differences can be observed in individuals at high risk, for example, with idiopathic rapid eye movement sleep behavior disorder, a prodromal condition of alpha-synuclein aggregation disorders including PD. OBJECTIVES: To compare microbiota in carefully preserved nasal wash and stool samples of subjects with idiopathic rapid eye movement sleep behavior disorder, manifest PD, and healthy individuals. METHODS: Microbiota of flash-frozen stool and nasal wash samples from 76 PD patients, 21 idiopathic rapid eye movement sleep behavior disorder patients, and 78 healthy controls were assessed by 16S and 18S ribosomal RNA amplicon sequencing. Seventy variables, related to demographics, clinical parameters including nonmotor symptoms, and sample processing, were analyzed in relation to microbiome variability and controlled differential analyses were performed. RESULTS: Differentially abundant gut microbes, such as Akkermansia, were observed in PD, but no strong differences in nasal microbiota. Eighty percent of the differential gut microbes in PD versus healthy controls showed similar trends in idiopathic rapid eye movement sleep behavior disorder, for example, Anaerotruncus and several Bacteroides spp., and correlated with nonmotor symptoms. Metagenomic sequencing of select samples enabled the reconstruction of genomes of so far uncharacterized differentially abundant organisms. CONCLUSION: Our study reveals differential abundances of gut microbial taxa in PD and its prodrome idiopathic rapid eye movement sleep behavior disorder in comparison to the healthy controls, and highlights the potential of metagenomics to identify and characterize microbial taxa, which are enriched or depleted in PD and/or idiopathic rapid eye movement sleep behavior disorder. (c) 2017 International Parkinson and Movement Disorder Society