Oral supplementation of nicotinamide riboside alters intestinal microbial composition in rats and mice, but not humans.

The gut microbiota impacts systemic levels of multiple metabolites including NAD+ precursors through diverse pathways. Nicotinamide riboside (NR) is an NAD+ precursor capable of regulating mammalian cellular metabolism. Some bacterial families express the NR-specific transporter, PnuC. We hypothesized that dietary NR supplementation would modify the gut microbiota across intestinal sections. We determined the effects of 12 weeks of NR supplementation on the microbiota composition of intestinal segments of high-fat diet-fed (HFD) rats. We also explored the effects of 12 weeks of NR supplementation on the gut microbiota in humans and mice. In rats, NR reduced fat mass and tended to decrease body weight. Interestingly, NR increased fat and energy absorption but only in HFD-fed rats. Moreover, 16S rRNA gene sequencing analysis of intestinal and fecal samples revealed an increased abundance of species within Erysipelotrichaceae and Ruminococcaceae families in response to NR. PnuC-positive bacterial strains within these families showed an increased growth rate when supplemented with NR. The abundance of species within the Lachnospiraceae family decreased in response to HFD irrespective of NR. Alpha and beta diversity and bacterial composition of the human fecal microbiota were unaltered by NR, but in mice, the fecal abundance of species within Lachnospiraceae increased while abundances of Parasutterella and Bacteroides dorei species decreased in response to NR. In conclusion, oral NR altered the gut microbiota in rats and mice, but not in humans. In addition, NR attenuated body fat mass gain in rats, and increased fat and energy absorption in the HFD context.

Dietary Protein Restriction Improves Metabolic Dysfunction in Patients with Metabolic Syndrome in a Randomized, Controlled Trial.

Dietary restriction (DR) reduces adiposity and improves metabolism in patients with one or more symptoms of metabolic syndrome. Nonetheless, it remains elusive whether the benefits of DR in humans are mediated by calorie or nutrient restriction. This study was conducted to determine whether isocaloric dietary protein restriction is sufficient to confer the beneficial effects of dietary restriction in patients with metabolic syndrome. We performed a prospective, randomized controlled dietary intervention under constant nutritional and medical supervision. Twenty-one individuals diagnosed with metabolic syndrome were randomly assigned for caloric restriction (CR; n = 11, diet of 5941 ± 686 KJ per day) or isocaloric dietary protein restriction (PR; n = 10, diet of 8409 ± 2360 KJ per day) and followed for 27 days. Like CR, PR promoted weight loss due to a reduction in adiposity, which was associated with reductions in blood glucose, lipid levels, and blood pressure. More strikingly, both CR and PR improved insulin sensitivity by 62.3% and 93.2%, respectively, after treatment. Fecal microbiome diversity was not affected by the interventions. Adipose tissue bulk RNA-Seq data revealed minor changes elicited by the interventions. After PR, terms related to leukocyte proliferation were enriched among the upregulated genes. Protein restriction is sufficient to confer almost the same clinical outcomes as calorie restriction without the need for a reduction in calorie intake. The isocaloric characteristic of the PR intervention makes this approach a more attractive and less drastic dietary strategy in clinical settings and has more significant potential to be used as adjuvant therapy for people with metabolic syndrome.

Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Metagenomic analysis of microbe-mediated vitamin metabolism in the human gut microbiome.

BACKGROUND: Human gut microbial communities have been known to produce vitamins, which are subsequently absorbed by the host in the large intestine. However, the relationship between species with vitamin pathway associated functional features or their gene abundance in different states of health and disease is lacking. Here, we analyzed shotgun fecal metagenomes of individuals from four different countries for genes that are involved in vitamin biosynthetic pathways and transport mechanisms and corresponding species' abundance. RESULTS: We found that the prevalence of these genes were found to be distributed across the dominant phyla of gut species. The number of positive correlations were high between species harboring genes related to vitamin biosynthetic pathways and transporter mechanisms than that with either alone. Although, the range of total gene abundances remained constant across healthy populations at the global level, species composition and their presence for metabolic pathway related genes determine the abundance and functional genetic content of vitamin metabolism. Based on metatranscriptomics data, the equation between abundance of vitamin-biosynthetic enzymes and vitamin-dependent enzymes suggests that the production and utilization potential of these enzymes seems way more complex usage allocations than just mere direct linear associations. CONCLUSIONS: Our findings provide a rationale to examine and disentangle the interrelationship between B-vitamin dosage (dietary or microbe-mediated) on gut microbial members and the host, in the gut microbiota of individuals with under- or overnutrition.

Gut microbiota dysbiosis is associated with malnutrition and reduced plasma amino acid levels: Lessons from genome-scale metabolic modeling.

Malnutrition is a severe non-communicable disease, which is prevalent in children from low-income countries. Recently, a number of metagenomics studies have illustrated associations between the altered gut microbiota and child malnutrition. However, these studies did not examine metabolic functions and interactions between individual species in the gut microbiota during health and malnutrition. Here, we applied genome-scale metabolic modeling to model the gut microbial species, which were selected from healthy and malnourished children from three countries. Our analysis showed reduced metabolite production capabilities in children from two low-income countries compared with a high-income country. Additionally, the models were also used to predict the community-level metabolic potentials of gut microbes and the patterns of pairwise interactions among species. Hereby we found that due to bacterial interactions there may be reduced production of certain amino acids in malnourished children compared with healthy children from the same communities. To gain insight into alterations in the metabolism of malnourished (stunted) children, we also performed targeted plasma metabolic profiling in the first 2 years of life of 25 healthy and 25 stunted children. Plasma metabolic profiling further revealed that stunted children had reduced plasma levels of essential amino acids compared to healthy controls. Our analyses provide a framework for future efforts towards further characterization of gut microbial metabolic capabilities and their contribution to malnutrition.

Human gut microbiota and healthy aging: Recent developments and future prospective.

The human gut microbiota alters with the aging process. In the first 2-3 years of life, the gut microbiota varies extensively in composition and metabolic functions. After this period, the gut microbiota demonstrates adult-like more stable and diverse microbial species. However, at old age, deterioration of physiological functions of the human body enforces the decrement in count of beneficial species (e.g. Bifidobacteria) in the gut microbiota, which promotes various gut-related diseases (e.g. inflammatory bowel disease). Use of plant-based diets and probiotics/prebiotics may elevate the abundance of beneficial species and prevent gut-related diseases. Still, the connections between diet, microbes, and host are only partially known. To this end, genome-scale metabolic modeling can help to explore these connections as well as to expand the understanding of the metabolic capability of each species in the gut microbiota. This systems biology approach can also predict metabolic variations in the gut microbiota during ageing, and hereby help to design more effective probiotics/prebiotics.

Genome-scale reconstruction of the metabolic network in Pseudomonas stutzeri A1501.

Pseudomonas stutzeri A1501 is an endophytic bacterium capable of nitrogen fixation. This strain has been isolated from the rice rhizosphere and provides the plant with fixed nitrogen and phytohormones. These interesting features encouraged us to study the metabolism of this microorganism at the systems-level. In this work, we present the first genome-scale metabolic model (iPB890) for P. stutzeri, involving 890 genes, 1135 reactions, and 813 metabolites. A combination of automatic and manual approaches was used in the reconstruction process. Briefly, using the metabolic networks of Pseudomonas aeruginosa and Pseudomonas putida as templates, a draft metabolic network of P. stutzeri was reconstructed. Then, the draft network was driven through an iterative and curative process of gap filling. In the next step, the model was evaluated using different experimental data such as specific growth rate, Biolog substrate utilization data and other experimental observations. In most of the evaluation cases, the model was successful in correctly predicting the cellular phenotypes. Thus, we posit that the iPB890 model serves as a suitable platform to explore the metabolism of P. stutzeri.

Modeling the differences in biochemical capabilities of pseudomonas species by flux balance analysis: how good are genome-scale metabolic networks at predicting the differences?

To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of three Pseudomonas metabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related to P. aeruginosa PAO1, P. putida KT2440, and P. fluorescens SBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable for in silico simulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare the in silico results to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.