The intestinal microbiome,probiotics and prebiotics in neurogastroenterology

The brain-gut axis allows bidirectional communication between the central nervous system (CNS) and the enteric nervous system (ENS), linking emotional and cognitive centers of the brain with peripheral intestinal functions. Recent experimental work suggests that the gut microbiota have an impact on the brain-gut axis. A group of experts convened by the International Scientific Association for Probiotics and Prebiotics (ISAPP) discussed the role of gut bacteria on brain functions and the implications for probiotic and prebiotic science. The experts reviewed and discussed current available data on the role of gut microbiota on epithelial cell function, gastrointestinal motility, visceral sensitivity, perception and behavior. Data, mostly gathered from animal studies, suggest interactions of gut microbiota not only with the enteric nervous system but also with the central nervous system via neural, neuroendocrine, neuroimmune and humoral links. Microbial colonization impacts mammalian brain development in early life and subsequent adult behavior. These findings provide novel insights for improved understanding of the potential role of gut microbial communities on psychological disorders, most particularly in the field of psychological comorbidities associated with functional bowel disorders like irritable bowel syndrome (IBS) and should present new opportunity for interventions with pro- and prebiotics.     

Rapid changes in the gut microbiome during human evolution

Humans are ecosystems containing trillions of microorganisms, but the evolutionary history of this microbiome is obscured by a lack of knowledge about microbiomes of African apes. We sequenced the gut communities of hundreds of chimpanzees, bonobos, and gorillas and developed a phylogenetic approach to reconstruct how present-day human microbiomes have diverged from those of ancestral populations. Compositional change in the microbiome was slow and clock-like during African ape diversification, but human microbiomes have deviated from the ancestral state at an accelerated rate. Relative to the microbiomes of wild apes, human microbiomes have lost ancestral microbial diversity while becoming specialized for animal-based diets. Individual wild apes cultivate more phyla, classes, orders, families, genera, and species of bacteria than do individual humans across a range of societies. These results indicate that humanity has experienced a depletion of the gut flora since diverging from Pan.The human microbiome is shaped by host genetics, environment, and lifestyle (1–3); thus, humanity''s unique evolutionary and cultural histories must have altered our associations with microorganisms (4). Despite intensive investigation of the microbiomes of humans spanning a range of geographic locations and cultures (5–7), how the composition of the microbiome has changed since humans diverged from other species, and since human populations diverged from one another, remains unclear, owing to a lack of knowledge about the microbiomes of ancestral hominid populations.Understanding how the composition of the human microbiome has changed over evolutionary time requires the inclusion of the microbiomes of phylogenetic outgroups (i.e., the African apes) into analyses of human microbiomes. Previous comparisons of the gut microbiomes of humans and the African apes have been restricted to just a few individuals per host species (8), precluding detection of the precise compositional differences that distinguish the microbiomes of the host species. Comparing the microbiomes of populations of chimpanzees, bonobos, gorillas, and humans while considering the phylogenetic relatedness among the hosts can reveal how the composition of the microbiome has changed since the host species diversified.Here we used a phylogenetic approach to identify the shifts in the composition of the microbiome that occurred along the lineages leading to the extant species of Homo and Pan. This analysis shows that humans across a range of cultures and geographies harbor microbiomes that are disproportionately divergent from those within wild apes. In particular, among the living hominid species, humans harbor uncharacteristically low levels of microbial diversity within their gut microbiomes.     

The human microbiome: opportunities and challenges for clinical care

There is a growing appreciation of the importance of the human microbiome to our normal physiology. This complex microbial ecosystem plays a range of roles, including influencing the development and function of our immune systems, providing essential nutrients, regulating metabolism and protecting us from opportunistic infections. Our increasing understanding of these processes is due, to a large extent, to the development of high‐throughput sequencing technologies, providing for the first time a means by which complex microbial dynamics can be detailed. There is also a growing recognition that disruption of commensal microbiota, a phenomenon known as dysbiosis, is associated with several common disorders, including inflammatory bowel disease, type 2 diabetes and oncogenesis. Further, where innate immunity fails to protect us, the microbial communities that colonise the external surfaces of our bodies represent a ready source of infection. This review discusses the mechanisms that govern our interaction with our resident microbiota, both in health and disease, the technological advances that allow us to gain insight into these relationships, and the way in which our growing understanding can inform clinical practice.     

The human gut microbiota: Metabolism and perspective in obesity

ABSTRACT

The gut microbiota has been recognized as an important factor in the development of metabolic diseases such as obesity and is considered an endocrine organ involved in the maintenance of energy homeostasis and host immunity. Dysbiosis can change the functioning of the intestinal barrier and the gut-associated lymphoid tissues (GALT) by allowing the passage of structural components of bacteria, such as lipopolysaccharides (LPS), which activate inflammatory pathways that may contribute to the development of insulin resistance. Furthermore, intestinal dysbiosis can alter the production of gastrointestinal peptides related to satiety, resulting in an increased food intake. In obese people, this dysbiosis seems be related to increases of the phylum Firmicutes, the genus Clostridium, and the species Eubacterium rectale, Clostridium coccoides, Lactobacillus reuteri, Akkermansia muciniphila, Clostridium histolyticum, and Staphylococcus aureus.     

A day in the life of the meta-organism: diurnal rhythms of the intestinal microbiome and its host

Life on Earth is dictated by circadian changes in the environment, caused by the planet's rotation around its own axis. All forms of life have evolved clock systems to adapt their physiology to the daily variations in geophysical parameters. The intestinal microbiome serves as a signaling hub in the communication between the host and its environment. We recently discovered that the microbiota undergoes diurnal oscillations in composition and function, and that these oscillations are required for metabolic homeostasis of the host. Here, we highlight these findings from the perspectives of microbial system stability and meta-organismal metabolic health. We also discuss the contribution of nutrition and biotic interventions on diurnal processes of the microbiota and their potential involvement in diseases commonly associated with circadian disruption.     

Experimental models of the gut microbiome

The human gut contains a diverse microbiota with large potential to influence health. Given the difficulty to access the main sites of the gut, in vitro models have been developed to dynamically monitor microbial processes at the site of metabolic activity. These models range from simple batch fermentations to complex multi-compartmental continuous systems. The latter include different models, focussing on similar but each also on distinct digestive parameters. The most intensively used include the three-stage continuous culture system, SHIME^®, EnteroMix, Lacroix model and TIM-2. Especially after inclusion of surface-attached mucosal microbes (M-SHIME), such models have been shown representative of the in vivo situation in terms of microbial composition and activity. They have even been shown to maintain the interpersonal variation among different human fecal inocula. Novel developments, such as the incorporation of host cells, will further broaden the potential of in vitro models to unravel the importance of gut microbes for human health and disease.     

A day in the life of the meta-organism: diurnal rhythms of the intestinal microbiome and its host

Life on Earth is dictated by circadian changes in the environment, caused by the planet''s rotation around its own axis. All forms of life have evolved clock systems to adapt their physiology to the daily variations in geophysical parameters. The intestinal microbiome serves as a signaling hub in the communication between the host and its environment. We recently discovered that the microbiota undergoes diurnal oscillations in composition and function, and that these oscillations are required for metabolic homeostasis of the host. Here, we highlight these findings from the perspectives of microbial system stability and meta-organismal metabolic health. We also discuss the contribution of nutrition and biotic interventions on diurnal processes of the microbiota and their potential involvement in diseases commonly associated with circadian disruption.     

Emerging science of the human microbiome

The human gastrointestinal tract hosts a large number of microbial cells which exceed their mammalian counterparts by approximately 3-fold. The genes expressed by these microorganisms constitute the gut microbiome and may participate in diverse functions that are essential to the host, including digestion, regulation of energy metabolism, and modulation of inflammation and immunity. The gut microbiome can be modulated by dietary changes, antibiotic use, or disease. Different ailments have distinct associated microbiomes in which certain species or genes are present in different relative quantities. Thus, identifying specific disease-associated signatures in the microbiome as well as the factors that alter microbial populations and gene expression will lead to the development of new products such as prebiotics, probiotics, antimicrobials, live biotherapeutic products, or more traditional drugs to treat these disorders. Gained knowledge on the microbiome may result in molecular lab tests that may serve as personalized tools to guide the use of the aforementioned products and monitor interventional progress.     

Elucidating the role of the host genome in shaping microbiome composition

A major goal of microbiome research is to identify the factors that determine bacterial composition within and upon a host. Environmental factors are thought to play a large role, such as diet in determining gut microbiome composition and moisture in determining skin microbiome composition. The role of host genetics, however, has been a source of debate in the literature. Recently, we examined the association of host genetics with human gut microbiome composition in the Hutterites, a population that lives and eats communally. We identified heritable bacterial taxa and host genetic loci associated with their abundances. In this addendum, I put these results into a broader context along with other recent studies of microbiome heritability, and synthesize common themes that appear across organisms and tissues, such as the relatively small extent genetics plays compared to environment and the role of host genetic variation in immune response and barrier integrity.     

In-feed antibiotic effects on the swine intestinal microbiome

Antibiotics have been administered to agricultural animals for disease treatment, disease prevention, and growth promotion for over 50 y. The impact of such antibiotic use on the treatment of human diseases is hotly debated. We raised pigs in a highly controlled environment, with one portion of the littermates receiving a diet containing performance-enhancing antibiotics [chlortetracycline, sulfamethazine, and penicillin (known as ASP250)] and the other portion receiving the same diet but without the antibiotics. We used phylogenetic, metagenomic, and quantitative PCR-based approaches to address the impact of antibiotics on the swine gut microbiota. Bacterial phylotypes shifted after 14 d of antibiotic treatment, with the medicated pigs showing an increase in Proteobacteria (1-11%) compared with nonmedicated pigs at the same time point. This shift was driven by an increase in Escherichia coli populations. Analysis of the metagenomes showed that microbial functional genes relating to energy production and conversion were increased in the antibiotic-fed pigs. The results also indicate that antibiotic resistance genes increased in abundance and diversity in the medicated swine microbiome despite a high background of resistance genes in nonmedicated swine. Some enriched genes, such as aminoglycoside O-phosphotransferases, confer resistance to antibiotics that were not administered in this study, demonstrating the potential for indirect selection of resistance to classes of antibiotics not fed. The collateral effects of feeding subtherapeutic doses of antibiotics to agricultural animals are apparent and must be considered in cost-benefit analyses.     

Microbiome‐immune‐metabolic axis in the epidemic of childhood obesity: Evidence and opportunities

Obesity epidemic responsible for increase in diabetes, heart diseases, infections and cancer shows no signs of abating. Obesity in children is also on rise, indicating the urgent need of strategies for prevention and intervention that must begin in early life. While originally posited that obesity results from the simple concept of consuming more calories, or genetics, emerging research suggests that the bacteria living in our gut (gut microbiome) and its interactions with immune cells and metabolic organs including adipose tissues (microbiome‐immune‐metabolic axis) play significant role in obesity development in childhood. Specifically, abnormal changes (dysbiosis) in the gut microbiome, stimulation of inflammatory cytokines, and shifts in the metabolic functions of brown adipose tissue and the browning of white adipose tissue are associated with increased obesity. Many factors from as early as gestation appear to contribute in obesity, such as maternal health, diet, antibiotic use by mother and/or child, and birth and feeding methods. Herein, using evidence from animal and human studies, we discuss how these factors impact microbiome‐immune‐metabolic axis and cause obesity epidemic in children, and describe the gaps in knowledge that are warranted for future research.     

CODY enables quantitatively spatiotemporal predictions on in vivo gut microbial variability induced by diet intervention

Microbial variations in the human gut are harbored in temporal and spatial heterogeneity, and quantitative prediction of spatiotemporal dynamic changes in the gut microbiota is imperative for development of tailored microbiome-directed therapeutics treatments, e.g. precision nutrition. Given the high-degree complexity of microbial variations, subject to the dynamic interactions among host, microbial, and environmental factors, identifying how microbiota colonize in the gut represents an important challenge. Here we present COmputing the DYnamics of microbiota (CODY), a multiscale framework that integrates species-level modeling of microbial dynamics and ecosystem-level interactions into a mathematical model that characterizes spatial-specific in vivo microbial residence in the colon as impacted by host physiology. The framework quantifies spatiotemporal resolution of microbial variations on species-level abundance profiles across site-specific colon regions and in feces, independent of a priori knowledge. We demonstrated the effectiveness of CODY using cross-sectional data from two longitudinal metagenomics studies—the microbiota development during early infancy and during short-term diet intervention of obese adults. For each cohort, CODY correctly predicts the microbial variations in response to diet intervention, as validated by available metagenomics and metabolomics data. Model simulations provide insight into the biogeographical heterogeneity among lumen, mucus, and feces, which provides insight into how host physical forces and spatial structure are shaping microbial structure and functionality.

Changes in the human gut microbiome composition are connected with development of numerous diseases, like obesity, type-2 diabetes, and immune dysfunction (1–3). Quantitative understanding and predicting how microbial variations are determined are crucial for designing microbiome-directed therapies that target chronic metabolic diseases (4, 5). However, this remains challenging due to the temporal and spatial heterogeneity along the human gut resulting from a dynamic interplay among host, microbial, and environmental conditions (6, 7). Diet is recognized as a controllable and pivotal environmental factor in shaping longitudinal microbial landscape development (8, 9), such as early childhood colonization (10) and long-term adulthood stabilization (11). While profiling of fecal samples enables a snapshot of consequential changes of the fecal microbiota in response to different stimuli, e.g. dietary changes (12–14), it is still far from describing the intrinsic dynamics of how microbiome colonize in the gut. Recently, the spatial heterogeneity of microbial composition between lumen and mucus has been recognized in mice (15, 16), but similar studies in humans is impossible with current techniques. In addition, measurements of absolute abundance profiles are required to correct the artifacts associated with relative abundance that confound revealing the interplay between microbial variations and health (17). Therefore, methods that enable quantifying the absolute, temporal, and spatial variations of in vivo human gut microbiota are needed to understand how to maintain or restore healthy microbiota.Computational models are widely used to decipher microbial complexity and response to perturbations (18). Most existing models have limited usage as they only address specific elements of the multidimensional interaction mechanisms. For example, similarity-based (19) and rule-mining models (20) describe microbial–microbial interactions without considering temporal dependency. The dynamic Bayesian model enables incorporation of directed interactions and longitudinal dataset (21), while reliance on training dataset and difficulties in model selection render these stochastic models confining to specific statistic condition and predictions are therefore not consistent and generalizable (22). The generalized Lotka–Volterra model (18, 23, 24) represents a step forward to simulate dynamics via formulating microbial growth rate as a lumped term, but adherence to assumptions of pairwise interactions-driven community dynamics and constant environment limits their predictive power. Genome-scale models (GEMs) (25) provide a valuable resource for studying structured microbial metabolism. With GEMs, microbial metabolic capacity, microbe–microbe interactions (26–28), microbial–diet interactions (12), and structural changes of two-species cocultures (29) are characterized using flux balance analysis (FBA). With rare exceptions, FBA requires a priori knowledge of metabolite uptake fluxes distributed among community members, with current limitations on these resources, faces challenges with modeling multispecies communities in a dynamic manner (30). Therefore, in adapting a computational framework that can simulate microbiome dynamics along the human gut, one encounters three challenges: 1) endogenously, the intrinsic dynamics not only emerge from the large number of microbiota components but also through the intricate and dynamic ways they interact (31, 32); 2) exogenously, the microbiota is exposed to a series of host–microbe metabolic axes (33), such as colonic physical forces (34), nascent colonization, and nutrient conditions; and 3) spatial structure of the in vivo microbiota localization plays a significant role impacting 1 and 2 (24).Here, we bridge the current theoretical gap by developing a multiscale framework for COmputing the DYnamics of gut microbiota (CODY), which enables identification and quantification of spatiotemporal-specific variations of gut microbiome absolute and relative abundance profiles, without a prior knowledge of microbiome interactions. We evaluated CODY’s performance by comparing model simulations with longitudinal changes in the microbial composition in fecal samples and in plasma metabolomics of two cohorts: 1) long-term development of the gut microbiome in early infancy and 2) short-term variation patterns of the gut microbiome in obese adults experiencing diet intervention. Comparison of model simulations with experimental data demonstrated predictive strength of the CODY modeling framework and hence lays the foundation for performing design of microbiome-directed therapeutics or of precision nutrition based on CODY simulations. The source code of CODY is freely available together with full documentation at https://github.com/JunGeng-Sysbio-Chalmers/CODY1.0_SourceCode.     

Reciprocal variations of nNOS and HSP90 are associated with fasting in gastrointestinal tract of the piglet

The effects of fasting on neuronal NO synthase (nNOS), Heme oxygenase 2 (HO-2), and heat shock protein 90 (HSP90) was determined by immunoblotting in the stomach, duodenum, mid-jejunum, distal ileum, and proximal colon of 28-day-old piglets. nNOS expression was drastically reduced in all the gastrointestinal areas studied while HO-2 was not changed. Concomitant with the nNOS decrease, elevated expressions of HSP90 were observed in these different areas. These results are discussed in terms of the regulation relationship between NOS and HSP90 and the possible protective effect of the heat shock protein and the potential application in digestive pathologies.     

An approach for evaluating the effects of dietary fiber polysaccharides on the human gut microbiome and plasma proteome

Increases in snack consumption associated with Westernized lifestyles provide an opportunity to introduce nutritious foods into poor diets. We describe two 10-wk-long open label, single group assignment human studies that measured the effects of two snack prototypes containing fiber preparations from two sustainable and scalable sources; the byproducts remaining after isolation of protein from the endosperm of peas and the vesicular pulp remaining after processing oranges for the manufacture of juices. The normal diets of study participants were supplemented with either a pea- or orange fiber-containing snack. We focused our analysis on quantifying the abundances of genes encoding carbohydrate-active enzymes (CAZymes) (glycoside hydrolases and polysaccharide lyases) in the fecal microbiome, mass spectrometric measurements of glycan structures (glycosidic linkages) in feces, plus aptamer-based assessment of levels of 1,300 plasma proteins reflecting a broad range of physiological functions. Computational methods for feature selection identified treatment-discriminatory changes in CAZyme genes that correlated with alterations in levels of fiber-associated glycosidic linkages; these changes in turn correlated with levels of plasma proteins representing diverse biological functions, including transforming growth factor type β/bone morphogenetic protein-mediated fibrosis, vascular endothelial growth factor-related angiogenesis, P38/MAPK-associated immune cell signaling, and obesity-associated hormonal regulators. The approach used represents a way to connect changes in consumer microbiomes produced by specific fiber types with host responses in the context of varying background diets.

Advances in our understanding of the role of the gut microbiome in regulating many aspects of human physiology hold the promise of evolving our view of human nutrition by establishing mechanistic connections between the foods we consume and how they affect health status. One manifestation of this effort is a series of studies, performed on well-phenotyped cohorts, that seek to relate features of gut microbial community composition (organisms, genes), dietary practices, and pre- and postprandial cardiometabolic responses to test meals (1–4). A key question raised by these initiatives relates to the nature of the “bioactive” components of foods. Specifically, what are the nutrients utilized by various gut community members or microbiome-encoded metabolic pathways? What products are produced by biotransformation of these nutrients? How are these products linked to specific host physiologic (or pathophysiologic) processes?Plant-derived dietary fibers represent a “poster child” for these efforts and illustrate the formidable challenges faced. The health benefits of dietary fibers are widely known, as is their inadequate representation in Western diets. However, natural fibers are structurally complex and highly diverse. They contain numerous, typically undefined polysaccharide structures and largely unspecified protein, lipid, and small molecule constituents. Their composition varies as a function of their origin (food staple and cultivar), the different methods employed to recover them from these sources, as well as the different techniques used to incorporate them into processed foods with acceptable organoleptic properties (5). Moreover, analyzing the host effects of metabolism of different fibers is confounded by the fact that there is substantial intra- and interpersonal variation in microbiome configuration (6, 7).Snacking is becoming an ever more dominant feature of daily life worldwide and thus provides an opportunity to introduce nutritious ingredients, such as fibers, into diets. However, obtaining structure-activity relationships for specific fiber types and their corresponding targets in the gut community is foundational for designing snack foods that evoke and/or reinforce microbiome responses that are beneficial to the host.Degradation of dietary polysaccharides is a function primarily performed by bacterial carbohydrate-active enzymes (CAZymes). The gut microbiome harbors tens of thousands of CAZyme genes belonging to at least 136 glycoside hydrolase (GH) and 29 polysaccharide lyase (PL) families [extrapolated and updated from El Kaoutari et al. (8)]. In contrast, the human genome only contains 98 GH and no PL genes (9), of which <20% contribute to the processing of dietary glycans.In the current study, we test the effects of dietary supplementation with two snack food prototypes, one containing pea fiber and the other orange fiber, in two pilot studies of overweight and obese individuals consuming their normal, unrestricted diets. Our strategy was to focus on fiber-associated changes in the abundances of microbial GH and PL genes to determine whether responses to the pea or orange fiber prototypes in the gut microbiome and host are decipherable against a background of varying dietary practices and starting microbiome configurations. Higher order singular value decomposition (10) was utilized as a feature selection tool to identify treatment-discriminating changes in GH and PL gene representation. Mass spectrometric assays of the levels of fecal glycan structures (glycosidic linkages) were subsequently performed and the results were correlated with changes in the abundances of treatment-discriminating GH and PL genes with known or predicted substrate specificities. Our analysis concluded by measuring changes in levels of 1,305 plasma proteins in each study participant as a function of fiber treatment and applying computational tools to identify links between these microbiome and plasma proteome changes in response to fiber consumption. Our results provide an approach, using pilot human studies, for selecting specific fiber preparations, plus informative microbiome and host biomarkers, that can be advanced to proof-of-concept clinical trials which assess their capacity for precise manipulation of microbiome and host features.     

Links between the gut microbiota,metabolism, and host behavior

ABSTRACT

The gut microbiota is known to regulate multiple aspects of host physiology, including metabolism and behavior. Locomotion, which is closely intertwined with metabolism, is an important component of complex behaviors, such as foraging, mating, and evading predators. Our recent work revealed that certain bacterial species and their products modulate motor behavior in the fruit fly Drosophila melanogaster via metabolic and neuronal pathways. In the context of our previously published findings and recent work by others, I will discuss potential avenues for future research at the intersection of the microbiota, metabolism, and host behavior.     

不同阿司匹林肠溶片对老年人上消化道黏膜影响的比较

目的 观察不同阿司匹林肠溶片对老年人上消化道黏膜的影响. 方法将我院近3年服用阿司匹林肠溶片(100 mg,1次/d)≥3个月、年龄>65岁的老年患者404例,按服用药物不同分为拜阿司匹灵组232例和普通阿司匹林肠溶片组172例,对两组患者的临床资料和胃镜检查结果进行比较,通过χ2检验,比较两种不同阿司匹林肠溶片对老年人上消化道影响的差异. 结果拜阿司匹灵组上消化道出血47例(20.3%),普通阿司匹林肠溶片组55例(32.0%),差异有统计学意义(χ2=7.19,P<0.01);拜阿司匹灵组胃镜检查显示胃、十二指肠炎症16例(6.9%),消化性溃疡8例(3.5%);普通阿司匹林肠溶片组分别为12例(7.0%)和36例(20.9%),检出消化性溃疡差异有统计学意义(χ2=31.10,P<0.01);胃肠道不良应发生率拜阿司匹灵组20例(8.6%),普通阿司匹林肠溶片组40例(23.3%),差异有统计学意义(χ2=16.73,P<0.01). 结论拜阿司匹灵对老年人上消化道的影响明显小于普通阿司匹林肠溶片,在临床上使用拜阿司匹灵比普通阿司匹林肠溶片更安全.     

Melatonin concentrations in serum and tissues of porcine gastrointestinal tract and their relationship to the intake and passage of food

Abstract: Melatonin concentrations were determined in serum and 10 segments of the gastrointestinal tract (GIT) of 48 pigs (100 kg weight). The animals were fasted for 30 hr and then sacrificed 0, 1,2, 5, 10, and 20 hr after refeeding. Peak amount of gastric digesta (2,428 g) and ileum digesta (850 g) were observed 1 hr and 5 hr, after refeeding, respectively. Conversely, colon content reached a minimal weight (726 g) at 2 hr after refeeding. Serum levels of melatonin increased from 3.4 pg/ml to 15.5 pg/ ml (peak 5 hr after refeeding). Melatonin levels in GIT tissues before refeeding varied from 23.8 pg/g (stomach-fundus) to 62.1 pg/g (rectum). Increasingly higher levels of melatonin were detected in the distal segments of the GIT. Higher melatonin levels after refeeding were observed in most GIT tissues except the rectum. In most tissues, peak melatonin values were detected 5 hr after refeeding. A significant change in weight of digesta across time ( P <0.05) was detected in the stomach, ileum, and cecum. Similar changes in melatonin levels across time were found in most tissues except the esophagus, stomach (cardia and pylorus), and rectum. Adjacent GIT tissues exhibited similar ( P <0.05) melatonin levels. The GIT melatonin levels correlated best with the variation of digesta weight in the ileum. In addition, the increase of serum melatonin levels correlated best with the increase of GIT melatonin levels in the distal part of the GIT. Our results suggest that melatonin produced in the ileum, cecum, and colon may contribute significantly to the short-term increase of serum melatonin levels observed after refeeding.     

Coevolution of yeast mannan digestion: Convergence of the civilized human diet,distal gut microbiome,and host immunity

The complex carbohydrates accessible to the distal gut microbiota (DGM) are key drivers in determining the structure of this ecosystem. Typically, plant cell wall polysaccharides and recalcitrant starch (i.e. dietary fiber), in addition to host glycans are considered the primary nutrients for the DGM; however, we recently demonstrated that α-mannans, highly branched polysaccharides that decorate the surface of yeast, are also nutrients for several members of Bacteroides spp. This relationship suggests that the advent of yeast in contemporary food technologies and the colonization of the intestine by endogenous fungi have roles in microbiome structure and function. Here we discuss the process of yeast mannan metabolism, and the intersection between various sources of intestinal fungi and their roles in recognition by the host innate immune system.