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Background and objectives: The gut microbiota performs many functions in the host organism, and metabolites derived from its activity, such as short-chain fatty acids (SCFA), are involved in immunometabolism. Alterations in gut microbial composition play an essential role in diseases such as heart failure, kidney disease, obesity, and diabetes mellitus. The current work aimed to analyze the associations of serum and fecal inflammatory biomarkers with the microbiota and SCFA in prediabetic subjects. Methods: 65 prediabetic patients, diagnosed according to the American Diabetes Association criteria, who participated in a randomized controlled intervention study with Moringa oleifera Lam. (2.4 g/day), were included. Inflammatory markers (Serum C reactive protein [CRP] and fecal calprotectin and sIgA), gut microbiota (qPCR), and short-chain fatty acids (SCFA; GC-FID) were studied before (V0) and after a 12-week intervention (V12). Relationships were explored using principal component analysis (PCA). Lineal regression models were performed to determine the predictive variables of inflammatory markers by including SCFA and gut microbiota groups as one block of independent variables. Fat mass percentage (BIA) and treatment group were used to adjust the models. Analyses were performed for V0 and V12 separately. Results: Only for calprotectin were significant models found at V0 (p = 0.044) and V12 (p = 0.010). Lactobacillus (standardized beta, β= 0.292; p = 0.047) and Bacteroides (β = 0.430; p = 0.009) groups were significant predictors at V0 and Lactobacillus (β = 0.339; p = 0.015) and the SCFA valeric acid (β = −0.533; p = 0.014) were predictors of calprotectin in V12. For CRP, a trend was found at V12 regression (p = 0.079), with significant contributions for the Blautia coccoides–Eubacterium rectale group (β = 0.585; p = 0.016) and the categoric

This study evaluated the intestinal effects of alkalinized filtered water in lean and obese adult Zucker rats. For 3 months, 12-week-old rats consumed either tap water or filtered alkalinized tap water from Madrid city. Weight gain was monitored, changes in metabolism were evaluated by indirect calorimetry, and total antioxidant capacity and levels of inflammatory mediators were measured in plasma. Feces were collected, their microbial composition was analyzed and histological analysis of the small and large intestine was performed, assessing the general state of the mucosa (MUC2), the inflammatory state (F4/80) and the presence of oxidative modifications in protein 4-Hydroxynonenal (4-HNE) by immunofluorescence (IF) and immunohistochemistry (IHC). The results obtained showed that the consumption of alkalinized filtered water improved the composition of the intestinal microbiome and the state of the intestinal mucosa, reducing both local and systemic inflammation and the level of oxidative stress. These changes were accompanied by a better maintenance of the oxidative status in rats. No differences were observed in antioxidant capacity nor in weight gain. The incorporation of probiotics in the diet had a significant impact on the microbiome. These effects were indicative of an improvement in general metabolic, oxidative and inflammatory status.

[Background]: For the last 25 years, the debate on the benefit–risk balance of moderate alcohol consumption has been ongoing. This study explored the relationships between the pattern of alcohol consumption and subjective quality of life in healthy adults., [Material and Methods]: Participants were 247 healthy adults aged 25–45 years, with a moderate alcohol consumption, classified in three groups of alcohol intake: None (N = 37; <0.7 g/day), Low (N = 87; 0.7–<5 g/day) and Medium (N = 123; 5–16 g/day in women and 5–28 g/day in men). Information was collected with questionnaires including: alcoholic beverage frequency and pattern, quality of life (SF-36v2), anxiety, depression, health condition, adherence to the Mediterranean diet, physical activity and sleep time., [Results]: Mean (SD) age of participants was 35.9 (6.3). In the Medium group, the mean alcohol intake was 10.98 ± 4.84 g/day on weekly bases and 24.7 ± 15.2 g/day on weekend days. Beer was the main contributor to total daily alcohol consumption. The percentage of subjects in the Medium group that showed a weekend average intake higher than moderate was 58.5% in exclusively weekend consumers and 48.2% in those who are not exclusive-weekend consumers (p = 0.278). Regarding markers of quality of life and mental health, the results did not show any significant association with alcohol consumption. In conclusion, in subjects that show weekly bases moderate intake of alcohol, weekend-day consumption levels can be high; however, no association of an overall moderate alcohol consumption pattern with quality of life was found.

Artificial sweeteners are additives widely used in our diet. Although there is no consensus, current evidence indicates that sucralose and saccharin could influence the gut microbiota. The aim of this study was to analyze the existing scientific evidence on the effects of saccharin and sucralose consumption on gut microbiota in humans. Different databases were used with the following search terms: sweeteners, non-caloric-sweeteners, sucralose, splenda, saccharin, sugartwin, sweet’n low, microbiota, gut microbiota, humans, animal model, mice, rats, and/or in vitro studies. In vitro and animal model studies indicate a dose-dependent relationship between the intake of both sweeteners and gut microbiota affecting both diversity and composition. In humans, long-term study suggests the existence of a positive correlation between sweetener consumption and some bacterial groups; however, most short-term interventions with saccharin and sucralose, in amounts below the ADI, found no significant effect on those groups, but there seems to be a different basal microbiota-dependent response of metabolic markers. Although studies in vitro and in animal models seem to relate saccharin and sucralose consumption to changes in the gut microbiota, more long-term studies are needed in humans considering the basal microbiota of participants and their dietary and lifestyle habits in all population groups. Toxicological and basal gut microbiota effects must be included as relevant factors to evaluate food safety and nutritional consequences of non-calorie sweeteners. In humans, doses, duration of interventions, and number of subjects included in the studies are key factors to interpret the results.

Different parts of the Moringa oleifera Lam. (MO) tree are consumed as food or food supplements for their nutritional and medicinal value; however, very few human studies have been published on the topic. The current work was aimed to provide ancillary analysis to the antidiabetic effects previously reported in a double-blind, randomized, placebo-controlled, parallel group intervention conducted in patients with prediabetes. Thus, the effect of MO leaves on blood and fecal inflammatory markers, serum lipid profile, plasma antioxidant capacity and blood pressure was studied in participants who consumed 6 × 400 mg capsule/day of MO dry leaf powder (MO, n = 31) or placebo (PLC, n = 34) over 12 weeks. Differences between groups were assessed using each biomarker’s change score with, adjustment for fat status and the baseline value. In addition, a decision tree analysis was performed to find individual characteristics influencing the glycemic response to MO supplementation. No differences in the biomarker’s change scores were found between the groups; however, the decision tree analysis revealed that plasma TNF-α was a significant predictor of the subject’s HbA1c response (improvement YES/NO; 77% correct classification) in the MO group. In conclusion, TNF-α seems to be a key factor to identify potential respondents to MO leaf powder.

There is increasing evidence that diet influences the relationship between gut microbiota and individual health outcomes. Nutrient intake affects the composition of the gut microbial community and provides metabolites that influence the host physiology. Dietary patterns, including macronutrient balance and feeding/fasting cycles which may be manipulated with dietary regimens based on caloric restriction periods, influence the gut homeostasis through its impact on the microbial ecosystem. Along the same line, prebiotic and probiotic ingredients and additives in foods, as well as the degree of food processing have consequences on gut microbiota and the related immune and metabolic response of the human host. Acquiring knowledge of these aspects, especially through an -omics-integral approach, might provide the basis for personalized nutritional interventions directed to avoid dysbiosis and contribute to the prevention of major chronic degenerative diseases. Despite vast scientific evidence supporting the relationship between dietary factors and gut microbiota composition and function, the underlying mechanisms and their potential impact are far from clear. There is a lack of well-designed longitudinal studies performed in target population groups whose dietary patterns can be particularly relevant for their future health, as is the case in infants, pregnant women, or athletes.

Moringa oleifera (MO) is a multipurpose plant with a high polyphenol content, which is being increasingly consumed to lessen the risk of chronic metabolic diseases such as Type 2 diabetes; however, scientific evidence from clinical trials is scarce. A double-blind, randomized, placebo-controlled, parallel group intervention study with MO leaves as a food supplement was conducted in subjects with prediabetes. They consumed six daily capsules of MO dry leaf powder (2400 mg/day) (MO, n = 31) or placebo (PLC, n = 34) over 12 weeks. Glycemia, appetite-controlling hormones and gut microbiota composition were studied. ANCOVA with the fixed factor “treatment” and the basal value as covariate was used to compare the change score between the groups. The results showed significant differences between groups in the rate of change of fasting blood glucose (FBG) and glycated hemoglobin (HbA1c), which showed opposite directions during the intervention, decreasing in MO and increasing in PLC. No different change scores were found between the groups in microbiota, hepatic and renal function markers or the appetite-controlling hormones measured. In conclusion, MO supplementation resulted in favorable changes in glycaemia markers compared to placebo in the subjects with prediabetes studied, suggesting that MO might act as a natural antihyperglycemic agent.

Moringa oleifera (MO) is a multipurpose plant consumed as food and known for its medicinal uses, among others. Leaves, seeds and pods are the main parts used as food or food supplements. Nutritionally rich and with a high polyphenol content in the form of phenolic acids, flavonoids and glucosinolates, MO has been shown to exert numerous in vitro activities and in vivo effects, including hypoglycemic activity. A systematic search was carried out in the PubMed database and reference lists on the effects of MO on glucose metabolism. Thirty-three animal studies and eight human studies were included. Water and organic solvent extracts of leaves and, secondly, seeds, have been extensively assayed in animal models, showing the hypoglycemic effect, both under acute conditions and in long-term administrations and also prevention of other metabolic changes and complications associated to the hyperglycemic status. In humans, clinical trials are scarce, with variable designs and testing mainly dry leaf powder alone or mixed with other foods or MO aqueous preparations. Although the reported results are encouraging, especially those from postprandial studies, more human studies are certainly needed with more stringent inclusion criteria and a sufficient number of diabetic or prediabetic subjects. Moreover, trying to quantify the bioactive substances administered with the experimental material tested would facilitate comparison between studies.

The dynamics and diversity of human gut microbiota that can remarkably influence the wellbeing and health of the host are constantly changing through the host’s lifetime in response to various factors. The aim of the present study was to determine a set of parameters that could have a major impact on classifying subjects into a single cluster regarding gut bacteria composition. Therefore, a set of demographical, environmental, and clinical data of healthy adults aged 25–50 years (117 female and 83 men) was collected. Fecal microbiota composition was characterized using Illumina MiSeq 16S rRNA gene amplicon sequencing. Hierarchical clustering was performed to analyze the microbiota data set, and a supervised machine learning model (SVM; Support Vector Machines) was applied for classification. Seventy variables from collected data were included in machine learning analysis. The agglomerative clustering algorithm suggested the presence of four distinct community types of most abundant bacterial phyla. Each cluster harbored a statistically significant different proportion of bacterial phyla. Regarding prediction, the most important features classifying subjects into clusters were measures of obesity (waist to hip ratio, BMI, and visceral fat index), total body water, blood pressure, energy intake, total fat, olive oil intake, total fiber intake, and water intake. In conclusion, the SVM model was shown as a valuable tool to classify healthy individuals based on their gut microbiota composition.

It is widely known that a good balance and healthy function for bacteria groups in the colon are necessary to maintain homeostasis and preserve health. However, the lack of consensus on what defines a healthy gut microbiota and the multitude of factors that influence human gut microbiota composition complicate the development of appropriate dietary recommendations for our gut microbiota. Furthermore, the varied response to the intake of probiotics and prebiotics observed in healthy adults suggests the existence of potential inter- and intra-individual factors, which might account for gut microbiota changes to a greater extent than diet. The changing dietary habits worldwide involving consumption of processed foods containing artificial ingredients, such as sweeteners; the coincident rise in emotional disorders; and the worsening of other lifestyle habits, such as smoking habits, drug consumption, and sleep, can together contribute to gut dysbiosis and health impairment, as well as the development of chronic diseases. This review summarizes the current literature on the effects of specific dietary ingredients (probiotics, prebiotics, alcohol, refined sugars and sweeteners, fats) in the gut microbiota of healthy adults and the potential inter- and intra-individual factors involved, as well as the influence of other potential lifestyle factors that are dramatically increasing nowadays.

The current study investigates whether probiotic fermented milk (PFM) and yogurt consumption (YC) are related to both the ingested bacteria taxa and the overall gut microbiota (GM) composition in healthy adults. PFM and YC habits were analyzed in 260 subjects (51% male) by specific questionnaires, and the following groups were considered: (1) PFM groups: nonconsumers (PFM-NC, n = 175) and consumers (PFM, n = 85), divided as follows: Bifidobacterium-containing PFM (Bif-PFM; n = 33), Lactobacillus-containing PFM (Lb-PFM; n = 14), and mixed Bifidobacterium and Lactobacillus-containing PFM (Mixed-PFM; n = 38); (2) PFM-NC were classified as: yogurt nonconsumers (Y-NC; n = 40) and yogurt consumers (n = 135). GM was analyzed through 16S rRNA sequencing. PFM consumers showed higher Bifidobacteria taxa levels compared to NC, from phylum through to species. Specifically, Bif-PFM consumption was related to higher B. animalis levels (p < 0.001), whereas Lb-PFM consumption was associated to higher levels of Bifidobacterium (p < 0.045) and B. longum (p = 0.011). YC was related to higher levels of the yogurt starter Streptococcus thermophilus (p < 0.001). Lactobacilli and the overall GM were not related either to YC or PFM consumption. According to these results, healthy adults might benefit from PFM intake by increasing Bifidobacterium levels.