Defining and Directing Gut Microbiota Maturation in Early Life: A Nutrition Perspective.

The development of the microbiome within the human digestive tract starts at birth and continues up to approximately 3 years of age when the microbial ecosystem resembles a more adulthood-like state. The pace of colonization and diversification of the gut microbiota in the early stages of life has been linked to short- and long-term health outcomes. Characterizing optimal maturation of the ecosystem may help identifying adverse events that impair the process and also factors that support and guide it, such as diet. To date, researchers have looked at the evolution over time of gut microbiota parameters such as diversity, taxa abundance, or specific functions. A more global approach has used "microbiota age" to capture maturation trajectory through machine learning models. In this review, the use and limitations of the latest methods to capture and understand microbiota maturation will be discussed. Then the role of nutrition in directing gut microbiota maturation in early life will be described together with the challenges that limit our comprehension of the effects of diet on the gut microbiota.

A distinct clade of Bifidobacterium longum in the gut of Bangladeshi children thrives during weaning.

The gut microbiome has an important role in infant health and development. We characterized the fecal microbiome and metabolome of 222 young children in Dhaka, Bangladesh during the first two years of life. A distinct Bifidobacterium longum clade expanded with introduction of solid foods and harbored enzymes for utilizing both breast milk and solid food substrates. The clade was highly prevalent in Bangladesh, present globally (at lower prevalence), and correlated with many other gut taxa and metabolites, indicating an important role in gut ecology. We also found that the B. longum clades and associated metabolites were implicated in childhood diarrhea and early growth, including positive associations between growth measures and B. longum subsp. infantis, indolelactate and N-acetylglutamate. Our data demonstrate geographic, cultural, seasonal, and ecological heterogeneity that should be accounted for when identifying microbiome factors implicated in and potentially benefiting infant development.

The complexities of the diet-microbiome relationship: advances and perspectives.

Personalised dietary modulation of the gut microbiota may be key to disease management. Current investigations provide a broad understanding of the impact of diet on the composition and activity of the gut microbiota, yet detailed knowledge in applying diet as an actionable tool remains limited. Further to the relative novelty of the field, approaches are yet to be standardised and extremely heterogeneous research outcomes have ensued. This may be related to confounders associated with complexities in capturing an accurate representation of both diet and the gut microbiota. This review discusses the intricacies and current methodologies of diet-microbial relations, the implications and limitations of these investigative approaches, and future considerations that may assist in accelerating applications. New investigations should consider improved collection of dietary data, further characterisation of mechanistic interactions, and an increased focus on -omic technologies such as metabolomics to describe the bacterial and metabolic activity of food degradation, together with its crosstalk with the host. Furthermore, clinical evidence with health outcomes is required before therapeutic dietary strategies for microbial amelioration can be made. The potential to reach detailed understanding of diet-microbiota relations may depend on re-evaluation, progression, and unification of research methodologies, which consider the complexities of these interactions.

Large-scale association analyses identify host factors influencing human gut microbiome composition.

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10-8) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10-20), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10-10 < P < 5 × 10-8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.

Epigenome-wide association study of diet quality in the Women's Health Initiative and TwinsUK cohort.

BACKGROUND: Diet quality is a risk factor for chronic disease and mortality. Differential DNA methylation across the epigenome has been associated with chronic disease risk. Whether diet quality is associated with differential methylation is unknown. This study assessed whether diet quality was associated with differential DNA methylation measured across 445 548 loci in the Women's Health Initiative (WHI) and the TwinsUK cohort. DESIGN: The discovery cohort consisted of 4355 women from the WHI. The replication cohort consisted of 571 mono- and dizygotic twins from the TwinsUK cohort. DNA methylation was measured in whole blood using the Illumina Infinium HumanMethylation450 Beadchip. Diet quality was assessed using the Alternative Healthy Eating Index 2010 (AHEI-2010). A meta-analysis, stratified by study cohort, was performed using generalized linear models that regressed methylation on AHEI-2010, adjusting for cell composition, chip number and location, study characteristics, principal components of genetic relatedness, age, smoking status, race/ethnicity and body mass index (BMI). Statistical significance was defined as a false discovery rate < 0.05. Significant sites were tested for replication in the TwinsUK cohort, with significant replication defined by P < 0.05 and a consistent direction. RESULTS: Diet quality was significantly associated with differential DNA methylation at 428 cytosine-phosphate-guanine (CpG) sites in the discovery cohort. A total of 24 CpG sites were consistent with replication in the TwinsUK cohort, more than would be expected by chance (P = 2.7x10-4), with one site replicated in both the blood and adipose tissue (cg16379999 located in the body of SEL1L). CONCLUSIONS: Diet quality was associated with methylation at 24 CpG sites, several of which have been associated with adiposity, inflammation and dysglycaemia. These findings may provide insight into pathways through which diet influences chronic disease.

A reference map of potential determinants for the human serum metabolome.

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.

Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes.

Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance and identified 13 taxa with disrupted rhythmicity in type 2 diabetes (T2D). Cross-validated prediction models based on this signature similarly classified T2D. In an independent cohort (FoCus), disruption of microbial oscillation and the model for T2D classification was confirmed in 1,363 subjects. This arrhythmic risk signature was able to predict T2D in 699 KORA subjects 5 years after initial sampling, being most effective in combination with BMI. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria. Thus, a cohort-specific risk pattern of arrhythmic taxa enables classification and prediction of T2D, suggesting a functional link between circadian rhythms and the microbiome in metabolic diseases.

Serum metabolites reflecting gut microbiome alpha diversity predict type 2 diabetes.

Type 2 diabetes (T2D) is associated with reduced gut microbiome diversity, although the cause is unclear. Metabolites generated by gut microbes also appear to be causative factors in T2D. We therefore searched for serum metabolites predictive of gut microbiome diversity in 1018 females from TwinsUK with concurrent metabolomic profiling and microbiome composition. We generated a Microbial Metabolites Diversity (MMD) score of six circulating metabolites that explained over 18% of the variance in microbiome alpha diversity. Moreover, the MMD score was associated with a significantly lower odds of prevalent (OR[95%CI] = 0.22[0.07;0.70], P = .01) and incident T2D (HR[95%CI] = 0.31[0.11,0.90], P = .03). We replicated our results in 1522 individuals from the ARIC study (prevalent T2D: OR[95%CI] = 0.79[0.64,0.96], P = .02, incident T2D: HR[95%CI] = 0.87[0.79,0.95], P = .003). The MMD score mediated 28%[15%,94%] of the total effect of gut microbiome on T2D after adjusting for confounders. Metabolites predicting higher microbiome diversity included 3-phenylpropionate(hydrocinnamate), indolepropionate, cinnamoylglycine and 5-alpha-pregnan-3beta,20 alpha-diol monosulfate(2) of which indolepropionate and phenylpropionate have already been linked to lower incidence of T2D. Metabolites correlating with lower microbial diversity included glutarate and imidazole propionate, of which the latter has been implicated in insulin resistance. Our results suggest that the effect of gut microbiome diversity on T2D is largely mediated by microbial metabolites, which might be modifiable by diet.

Self-Reported Symptoms of COVID-19, Including Symptoms Most Predictive of SARS-CoV-2 Infection, Are Heritable.

Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n = 3261) completing the C-19 COVID-19 symptom tracker app allowed classical twin studies of COVID-19 symptoms, including predicted COVID-19, a symptom-based algorithm to predict true infection, derived from app users tested for SARS-CoV-2. We found heritability of 49% (32-64%) for delirium; 34% (20-47%) for diarrhea; 31% (8-52%) for fatigue; 19% (0-38%) for anosmia; 46% (31-60%) for skipped meals and 31% (11-48%) for predicted COVID-19. Heritability estimates were not affected by cohabiting or by social deprivation. The results suggest the importance of host genetics in the risk of clinical manifestations of COVID-19 and provide grounds for planning genome-wide association studies to establish specific genes involved in viral infectivity and the host immune response.

Effect of Diet on the Gut Microbiota: Rethinking Intervention Duration.

The human gut is inhabited by trillions of microorganisms composing a dynamic ecosystem implicated in health and disease. The composition of the gut microbiota is unique to each individual and tends to remain relatively stable throughout life, yet daily transient fluctuations are observed. Diet is a key modifiable factor influencing the composition of the gut microbiota, indicating the potential for therapeutic dietary strategies to manipulate microbial diversity, composition, and stability. While diet can induce a shift in the gut microbiota, these changes appear to be temporary. Whether prolonged dietary changes can induce permanent alterations in the gut microbiota is unknown, mainly due to a lack of long-term human dietary interventions, or long-term follow-ups of short-term dietary interventions. It is possible that habitual diets have a greater influence on the gut microbiota than acute dietary strategies. This review presents the current knowledge around the response of the gut microbiota to short-term and long-term dietary interventions and identifies major factors that contribute to microbiota response to diet. Overall, further research on long-term diets that include health and microbiome measures is required before clinical recommendations can be made for dietary modulation of the gut microbiota for health.

Interplay between the human gut microbiome and host metabolism.

The human gut is inhabited by a complex and metabolically active microbial ecosystem. While many studies focused on the effect of individual microbial taxa on human health, their overall metabolic potential has been under-explored. Using whole-metagenome shotgun sequencing data in 1,004 twins, we first observed that unrelated subjects share, on average, almost double the number of metabolic pathways (82%) than species (43%). Then, using 673 blood and 713 faecal metabolites, we found metabolic pathways to be associated with 34% of blood and 95% of faecal metabolites, with over 18,000 significant associations, while species showed less than 3,000 associations. Finally, we estimated that the microbiome was involved in a dialogue between 71% of faecal, and 15% of blood, metabolites. This study underlines the importance of studying the microbial metabolic potential rather than focusing purely on taxonomy to find therapeutic and diagnostic targets, and provides a unique resource describing the interplay between the microbiome and the systemic and faecal metabolic environments.

Dissecting the role of the gut microbiota and diet on visceral fat mass accumulation.

Both gut microbiota and diet have been shown to impact visceral fat mass (VFM), a major risk factor for cardiometabolic disease, but their relative contribution has not been well characterised. We aimed to estimate and separate the effect of gut microbiota composition from that of nutrient intake on VFM in 1760 older female twins. Through pairwise association analyses, we identified 93 operational taxonomic units (OTUs) and 10 nutrients independently linked to VFM (FDR < 5%). Conditional analyses revealed that the majority (87%) of the 93 VFM-associated OTUs remained significantly associated with VFM irrespective of nutrient intake correction. In contrast, we observed that the effect of fibre, magnesium, biotin and vitamin E on VFM was partially mediated by OTUs. Moreover, we estimated that OTUs were more accurate predictors of VFM than nutrients and accounted for a larger percentage of its variance. Our results suggest that while the role of certain nutrients on VFM appears to depend on gut microbiota composition, specific gut microbes may affect host adiposity regardless of dietary intake. The findings imply that the gut microbiota may have a greater contribution towards shaping host VFM than diet alone. Thus, microbial-based therapy should be prioritised for VFM reduction in overweight and obese subjects.

Relationship between faecal microbiota and plasma metabolome in rats fed NK603 and MON810 GM maize from the GMO90+ study.

Safety concerns arising from the consumption of foods derived from genetically modified (GM) crops remains a controversial subject. We report here a faecal microbiota compositional analysis in Wistar rats from the GMO90 + study, which fed glyphosate-tolerant NK603 (+/- Roundup application) and Bt toxin MON810 GM maize for 6 months in comparison to their closest non-GM isogenic lines. We first integrated the faecal microbiota compositional data with results from plasma metabolomics to understand which bacterial species can influence host metabolism. Coriobacteriaceae and Acetatifactor significantly predicted plasma metabolic profile in males, while Bifidobacterium and Ruminococcus were able to predict female plasma metabolites. We then investigated the differences in fecal microbiota composition between group of rats fed MON810 or NK603 GM maize in comparison to their isogenic lines. Bacterial community richness was not altered by the test diets. There were no statistically significant differences in taxa abundance in the rat faecal microbiota that we could attribute to the consumption of either MON810 or NK603. We show that the consumption of the widely cultivated GM maize varieties NK603 and MON810 even up to 33% of the total diet had no effect on the status of the faecal microbiota compared to non-GM near isogenic lines.

Socioeconomic Status and the Gut Microbiome: A TwinsUK Cohort Study.

Socioeconomic inequalities in health and mortality are well established, but the biological mechanisms underlying these associations are less understood. In parallel, the gut microbiome is emerging as a potentially important determinant of human health, but little is known about its broader environmental and social determinants. We test the association between gut microbiota composition and individual- and area-level socioeconomic factors in a well-characterized twin cohort. In this study, 1672 healthy volunteers from twin registry TwinsUK had data available for at least one socioeconomic measure, existing fecal 16S rRNA microbiota data, and all considered co-variables. Associations with socioeconomic status (SES) were robust to adjustment for known health correlates of the microbiome; conversely, these health-microbiome associations partially attenuated with adjustment for SES. Twins discordant for IMD (Index of Multiple Deprivation) were shown to significantly differ by measures of compositional dissimilarity, with suggestion the greater the difference in twin pair IMD, the greater the dissimilarity of their microbiota. Future research should explore how SES might influence the composition of the gut microbiota and its potential role as a mediator of differences associated with SES.

Heritable components of the human fecal microbiome are associated with visceral fat.

Obesity and its associated diseases are one of the major causes of death worldwide. The gut microbiota has been identified to have essential regulatory effects on human metabolism and obesity in particular. In a recent study we provided some insights into the link between the gut microbiota (GM) and adiposity, as well as host genetic modulation of these processes. Our results identify novel evidence of association between 6 adiposity phenotypes and faecal microbial operational taxonomic units (OTUs). Accumulation of visceral fat, a key risk factor for cardio-metabolic disease, has the strongest and most pervasive signature on the gut microbiota of the factors we examined. Furthermore, we observe that the adiposity-associated OTUs were classified as heritable and in some cases were also associated with host genetic variation at obesity-associated human candidate genes FHIT, TDRG1 and ELAVL4. This addendum confirms our previously published results in the TwinsUK cohort using a different approach to OTU clustering and multivariate analysis, and discusses further the importance of considering the GM as a complex ecosystem.

The Inositol-3-Phosphate Synthase Biosynthetic Enzyme Has Distinct Catalytic and Metabolic Roles.

Inositol levels, maintained by the biosynthetic enzyme inositol-3-phosphate synthase (Ino1), are altered in a range of disorders, including bipolar disorder and Alzheimer's disease. To date, most inositol studies have focused on the molecular and cellular effects of inositol depletion without considering Ino1 levels. Here we employ a simple eukaryote, Dictyostelium discoideum, to demonstrate distinct effects of loss of Ino1 and inositol depletion. We show that loss of Ino1 results in an inositol auxotrophy that can be rescued only partially by exogenous inositol. Removal of inositol supplementation from the ino1(-) mutant resulted in a rapid 56% reduction in inositol levels, triggering the induction of autophagy, reduced cytokinesis, and substrate adhesion. Inositol depletion also caused a dramatic generalized decrease in phosphoinositide levels that was rescued by inositol supplementation. However, loss of Ino1 triggered broad metabolic changes consistent with the induction of a catabolic state that was not rescued by inositol supplementation. These data suggest a metabolic role for Ino1 that is independent of inositol biosynthesis. To characterize this role, an Ino1 binding partner containing SEL1L1 domains (Q54IX5) and having homology to mammalian macromolecular complex adaptor proteins was identified. Our findings therefore identify a new role for Ino1, independent of inositol biosynthesis, with broad effects on cell metabolism.

Synbiotic approach restores intestinal homeostasis and prolongs survival in leukaemic mice with cachexia.

Cancer cachexia is a multifactorial syndrome that includes muscle wasting and inflammation. As gut microbes influence host immunity and metabolism, we investigated the role of the gut microbiota in the therapeutic management of cancer and associated cachexia. A community-wide analysis of the caecal microbiome in two mouse models of cancer cachexia (acute leukaemia or subcutaneous transplantation of colon cancer cells) identified common microbial signatures, including decreased Lactobacillus spp. and increased Enterobacteriaceae and Parabacteroides goldsteinii/ASF 519. Building on this information, we administered a synbiotic containing inulin-type fructans and live Lactobacillus reuteri 100-23 to leukaemic mice. This treatment restored the Lactobacillus population and reduced the Enterobacteriaceae levels. It also reduced hepatic cancer cell proliferation, muscle wasting and morbidity, and prolonged survival. Administration of the synbiotic was associated with restoration of the expression of antimicrobial proteins controlling intestinal barrier function and gut immunity markers, but did not impact the portal metabolomics imprinting of energy demand. In summary, this study provided evidence that the development of cancer outside the gut can impact intestinal homeostasis and the gut microbial ecosystem and that a synbiotic intervention, by targeting some alterations of the gut microbiota, confers benefits to the host, prolonging survival and reducing cancer proliferation and cachexia.

Brachyspira pilosicoli-induced avian intestinal spirochaetosis.

Avian intestinal spirochaetosis (AIS) is a common disease occurring in poultry that can be caused by Brachyspira pilosicoli, a Gram-negative bacterium of the order Spirochaetes. During AIS, this opportunistic pathogen colonises the lower gastrointestinal (GI) tract of poultry (principally, the ileum, caeca, and colon), which can cause symptoms such as diarrhoea, reduced growth rate, and reduced egg production and quality. Due to the large increase of bacterial resistance to antibiotic treatment, the European Union banned in 2006 the prophylactic use of antibiotics as growth promoters in livestock. Consequently, the number of outbreaks of AIS has dramatically increased in the UK resulting in significant economic losses. This review summarises the current knowledge about AIS infection caused by B. pilosicoli and discusses various treatments and prevention strategies to control AIS.

New insights into the impact of Lactobacillus population on host-bacteria metabolic interplay.

We aimed at evaluating the association between intestinal Lactobacillus sp. composition and their metabolic activity with the host metabolism in adult and elderly individuals. Faecal and plasma metabolites were measured and correlated to the Lactobacillus species distribution in healthy Estonian cohorts of adult (n = 16; < 48 y) and elderly (n = 33; > 65 y). Total cholesterol, LDL, C-reactive protein and glycated hemoglobin were statistically higher in elderly, while platelets, white blood cells and urinary creatinine were higher in adults. Aging was associated with the presence of L. paracasei and L. plantarum and the absence of L. salivarius and L. helveticus. High levels of intestinal Lactobacillus sp. were positively associated with increased concentrations of faecal short chain fatty acids, lactate and essential amino acids. In adults, high red blood cell distribution width was positively associated with presence of L. helveticus and absence of L. ruminis. L. helveticus was correlated to lactate and butyrate in faecal waters. This indicates a strong relationship between the composition of the gut Lactobacillus sp. and host metabolism. Our results confirm that aging is associated with modulations of blood biomarkers and intestinal Lactobacillus species composition. We identified specific Lactobacillus contributions to gut metabolic environment and related those to blood biomarkers. Such associations may prove useful to decipher the biological mechanisms underlying host-gut microbial metabolic interactions in an ageing population.