Impact of fibre supplementation on microbiome and resilience in healthy participants: A randomized, placebo-controlled clinical trial.

BACKGROUND AND AIMS: The gut microbiome exerts important roles in health, e.g., functions in metabolism and immunology. These functions are often exerted via short-chain fatty acid (SCFA) production by gut bacteria. Studies demonstrating causal relationships between interventions targeting the microbiome and clinical outcomes are limited. This study aimed to show a causal relationship between microbiome modulation through fibre intervention and health. METHODS AND RESULTS: This randomized, double-blind, cross-over study included 65 healthy subjects, aged 45-70 years, with increased metabolic risk (i.e., body mass index [BMI] 25-30 kg/m2, low to moderate daily dietary fibre intake, <30g/day). Subjects took daily a fibre mixture of Acacia gum and carrot powder or placebo for 12 weeks, with an 8-week wash-out period. Faecal samples for measurement of SCFAs and microbiome analysis were collected every 4 weeks. Before and after each intervention period subjects underwent the mixed-meal PhenFlex challenge Test (PFT). Health effects were expressed as resilience to the stressors of the PFT and as fasting metabolic and inflammatory state. The fibre mixture exerted microbiome modulation, with an increase in ß-diversity (p < 0.001). α-diversity was lower during fibre mixture intake compared to placebo after 4, 8 and 12 weeks (p = 0.002; p = 0.012; p = 0.031). There was no effect observed on faecal SCFA concentrations, nor on any of the primary clinical outcomes (Inflammatory resilience: p = 0.605, Metabolic resilience: p = 0.485). CONCLUSION: Although the intervention exerted effects on gut microbiome composition, no effects on SCFA production, on resilience or fasting metabolic and inflammatory state were observed in this cohort. REGISTRATION NUMBER CLINICALTRIALS.GOV: NCT04829396.

Individual and Group-Based Effects of In Vitro Fiber Interventions on the Fecal Microbiota.

The development of microbiome-targeted strategies is limited by individual differences in gut microbiome composition and metabolic responses to interventions. In vitro models that can replicate this variation allow us to conduct pre-clinical studies and assess efficacy. This study describes the exposure of 16 individual fecal microbiota samples to 5 different fibers using an in vitro system for the anaerobic cultivation of bacteria. The individual microbiota differed in composition and metabolite profiles (short-chain fatty acids and branched-chain fatty acids) after incubation with the fibers. Furthermore, microbiota composition after fiber incubation was significantly different between subjects with good intestinal health and subjects with Inflammatory Bowel Disease (IBD). α-diversity was differently affected by dietary fibers; for example, exposure to psyllium resulted in increased diversity in the healthy group and in decreased diversity in the IBD group. Instead, the functional metabolic profile did not differ between the two groups. Finally, the combination of all fibers, tested on the microbiota from IBD subjects, resulted in stronger overall effects on both microbiota composition and metabolite production compared to the single fibers. These results confirm that incubation with dietary fiber results in different compositional and functional effects on individual microbiota and that in vitro models represent successful tools for studying individual fiber effects.

2'-Fucosyllactose inhibits proliferation of Clostridioides difficile ATCC 43599 in the CDi-screen, an in vitro model simulating Clostridioides difficile infection.

Background: Clostridioides difficile is a Gram-positive anaerobic bacterium that can produce the toxins TcdA and/or TcdB and is considered an opportunistic pathogen. C. difficile is mainly transmitted as endospores, which germinate to produce the pathogenic vegetative cells under suitable conditions in the gut. To efficiently screen novel therapeutic- interventions against the proliferation of C. difficile within a complex microbial community, platforms are needed that facilitate parallel experimentation. In order to allow for screening of novel interventions a medium-to-high throughput in vitro system is desirable. To this end, we have developed the 96-well CDi-screen platform that employs an adapted simulated ileal effluent medium (CDi-SIEM) and allows for culturing of pathogenic C. difficile. Methods: C. difficile strain ATCC 43599 was inoculated in the form of vegetative cells and spores into the CDi-screen in the presence and absence of a cultured fecal microbiota and incubated for 48h. To demonstrate its utility, we investigated the effect of the human milk oligosaccharide 2'-Fucosyllactose (2'-FL) at 4 and 8 mg/mL on C. difficile outgrowth and toxin production in the CDi-screen. The test conditions were sampled after 24 and 48 hours. C. difficile -specific primers were used to monitor C. difficile growth via qPCR and barcoded 16S rRNA gene amplicon sequencing facilitated the in-depth analysis of gut microbial community dynamics. Results: C. difficile ATCC 43599 proliferated in CDi-SIEM, both when inoculated as spores and as vegetative cells. The strain reached cell numbers expressed as C. difficile genome equivalents of up to 10 8 cells per mL after 24h of incubation. 2'-FL significantly inhibited the outgrowth of the ATTC 43599 strain within a complex human gut microbial community in the CDi-screen. In addition, a dose-dependent modulation of the gut microbial community composition by 2'-FL supplementation was detected, with a significant increase in the relative abundance of the genus Blautia in the presence of 2'-FL. Conclusion: The CDi-screen is suitable for studying C. difficile proliferation in a complex gut ecosystem and for screening for anti-pathogenic interventions that target C. difficile directly and/or indirectly through interactions with the gut microbiota. Different doses of compounds such as in this study the dose of the human milk oligosaccharide 2'-FL can be screened for efficacy in the inhibition of C. difficile proliferation.

Digital Biomarkers for Personalized Nutrition: Predicting Meal Moments and Interstitial Glucose with Non-Invasive, Wearable Technologies.

Digital health technologies may support the management and prevention of disease through personalized lifestyle interventions. Wearables and smartphones are increasingly used to continuously monitor health and disease in everyday life, targeting health maintenance. Here, we aim to demonstrate the potential of wearables and smartphones to (1) detect eating moments and (2) predict and explain individual glucose levels in healthy individuals, ultimately supporting health self-management. Twenty-four individuals collected continuous data from interstitial glucose monitoring, food logging, activity, and sleep tracking over 14 days. We demonstrated the use of continuous glucose monitoring and activity tracking in detecting eating moments with a prediction model showing an accuracy of 92.3% (87.2-96%) and 76.8% (74.3-81.2%) in the training and test datasets, respectively. Additionally, we showed the prediction of glucose peaks from food logging, activity tracking, and sleep monitoring with an overall mean absolute error of 0.32 (+/-0.04) mmol/L for the training data and 0.62 (+/-0.15) mmol/L for the test data. With Shapley additive explanations, the personal lifestyle elements important for predicting individual glucose peaks were identified, providing a basis for personalized lifestyle advice. Pending further validation of these digital biomarkers, they show promise in supporting the prevention and management of type 2 diabetes through personalized lifestyle recommendations.

Vitamin D supplementation in chronic obstructive pulmonary disease patients with low serum vitamin D: a randomized controlled trial.

BACKGROUND: Vitamin D deficiency is frequently found in patients with chronic obstructive pulmonary disease (COPD). Vitamin D has antimicrobial, anti-inflammatory, and immunomodulatory effects. Therefore, supplementation may prevent COPD exacerbations, particularly in deficient patients. OBJECTIVES: We aimed to assess the effect of vitamin D supplementation on exacerbation rate in vitamin D-deficient patients with COPD. METHODS: We performed a multicenter, double-blind, randomized controlled trial. COPD patients with ≥1 exacerbations in the preceding year and a vitamin D deficiency (15-50 nmol/L) were randomly allocated in a 1:1 ratio to receive either 16,800 International Units (IU) vitamin D3 or placebo once a week during 1 y. Primary outcome of the study was exacerbation rate. Secondary outcomes included time to first and second exacerbations, time to first and second hospitalizations, use of antibiotics and corticosteroids, pulmonary function, maximal respiratory mouth pressure, physical performance, skeletal muscle strength, systemic inflammatory markers, nasal microbiota composition, and quality of life. RESULTS: The intention-to-treat population consisted of 155 participants. Mean ± SD serum 25-hydroxyvitamin D [25(OH)D] concentration after 1 y was 112 ± 34 nmol/L in the vitamin D group, compared with 42 ± 17 nmol/L in the placebo group. Vitamin D supplementation did not affect exacerbation rate [incidence rate ratio (IRR): 0.90; 95% CI: 0.67, 1.21]. In a prespecified subgroup analysis in participants with 25(OH)D concentrations of 15-25 nmol/L (n = 31), no effect of vitamin D supplementation was found (IRR: 0.91; 95% CI: 0.43, 1.93). No relevant differences were found between the intervention and placebo groups in terms of secondary outcomes. CONCLUSIONS: Vitamin D supplementation did not reduce exacerbation rate in COPD patients with a vitamin D deficiency.This trial was registered at clinicaltrials.gov as NCT02122627.

Linking Categorical and Dimensional Approaches to Assess Food-Related Emotions.

Reflecting the two main prevailing and opposing views on the nature of emotions, emotional responses to food and beverages are typically measured using either (a) a categorical (lexicon-based) approach where users select or rate the terms that best express their food-related feelings or (b) a dimensional approach where they rate perceived food items along the dimensions of valence and arousal. Relating these two approaches is problematic since a response in terms of valence and arousal is not easily expressed in terms of emotions (like happy or disgusted). In this study, we linked the dimensional approach to a categorical approach by establishing mapping between a set of 25 emotion terms (EsSense25) and the valence-arousal space (via the EmojiGrid graphical response tool), using a set of 20 food images. In two 'matching' tasks, the participants first imagined how the food shown in a given image would make them feel and then reported either the emotional terms or the combination of valence and arousal that best described their feelings. In two labeling tasks, the participants first imagined experiencing a given emotion term and then they selected either the foods (images) that appeared capable to elicit that feeling or reported the combination of valence and arousal that best reflected that feeling. By combining (1) the mapping between the emotion terms and the food images with (2) the mapping of the food images to the valence-arousal space, we established (3) an indirect (via the images) mapping of the emotion terms to the valence-arousal space. The results show that the mapping between terms and images was reliable and that the linkages have straightforward and meaningful interpretations. The valence and arousal values that were assigned to the emotion terms through indirect mapping to the valence-arousal space were typically less extreme than those that were assigned through direct mapping.

The Skin and Nose Microbiome and Its Association with Filaggrin Gene Mutations in Pediatric Atopic Dermatitis.

BACKGROUND: Interactions between the skin barrier, immune system, and microbiome underlie the development of atopic dermatitis (AD). OBJECTIVE: To investigate the skin and nasal microbiome in relation to filaggrin gene (FLG) mutations. METHODS: A cross-sectional study including 77 children with difficult-to-treat AD. The entire encoding region of FLG was screened for mutations using single molecule molecular inversion probes and next-generation sequencing. Bacterial swabs from the anterior nares, lesional and nonlesional skin were analyzed using 16S rRNA sequencing. For skin samples, additional qPCR was performed for Staphylococcus aureus and Staphylococcus epidermidis. RESULTS: The prevalence of patients with a mutation in FLG was 40%, including 10 different mutations. Analyzing bacterial swabs from all three niches showed a significant effect for both niche and FLG mutation status on the overall microbiome composition. Using a subset analysis to test the effect of FLG mutation status per niche separately did not show a significant association to the microbiome. Shannon diversity and S. aureus abundance were significantly affected by the niche, but not by the presence of an FLG mutation. CONCLUSIONS: Our results suggest only a minor role for FLG mutation status on the overall microbiome, which is rather caused by differences in the present genera than by microbe richness and evenness.

An altered microbiota pattern precedes Type 2 diabetes mellitus development: From the CORDIOPREV study.

Introduction: A distinctive gut microbiome have been linked to type 2 diabetes mellitus (T2DM). Objectives: We aimed to evaluate whether gut microbiota composition, in addition to clinical biomarkers, could improve the prediction of new incident cases of diabetes in patients with coronary heart disease. Methods: All the patients from the CORDIOPREV (Clinical Trials.gov.Identifier: NCT00924937) study without T2DM at baseline were included (n = 462). Overall, 107 patients developed it after a median of 60 months. The gut microbiota composition was determined by 16S rRNA gene sequencing and predictive models were created using hold-out method. Results: A gut microbiota profile associated with T2DM development was determined through a microbiome-based predictive model. The addition of microbiome data to clinical parameters (variables included in FINDRISC risk score and the diabetes risk score of the American Diabetes Association, HDL, triglycerides and HbA1c) improved the prediction increasing the area under the curve from 0.632 to 0.946. Furthermore, a microbiome-based risk score including the ten most discriminant genera, was associated with the probability of develop T2DM. Conclusion: These results suggest that a microbiota profile is associated to the T2DM development. An integrate predictive model of microbiome and clinical data that can improve the prediction of T2DM is also proposed, if is validated in independent populations to prevent this disease.

Associations of the oral microbiota and Candida with taste, smell, appetite and undernutrition in older adults.

Poor taste and smell function are widely thought to contribute to the development of poor appetite and undernutrition in older adults. It has been hypothesized that the oral microbiota play a role as well, but evidence is scarce. In a cross-sectional cohort of 356 older adults, we performed taste and smell tests, collected anthropometric measurements and tongue swabs for analysis of microbial composition (16S rRNA sequencing) and Candida albicans abundance (qPCR). Older age, edentation, poor smell and poor appetite were associated with lower alpha diversity and explained a significant amount of beta diversity. Moreover, a lower Streptococcus salivarius abundance was associated with poor smell identification score, whereas high C. albicans abundance seemed to be associated with poor smell discrimination score. In our population, neither the tongue microbiota, nor C. albicans were associated with poor taste or directly with undernutrition. Our findings do suggest a host-microbe interaction with regard to smell perception and appetite.

A Machine Learning Algorithm for Quantitatively Diagnosing Oxidative Stress Risks in Healthy Adult Individuals Based on Health Space Methodology: A Proof-of-Concept Study Using Korean Cross-Sectional Cohort Data.

Oxidative stress aggravates the progression of lifestyle-related chronic diseases. However, knowledge and practices that enable quantifying oxidative stress are still lacking. Here, we performed a proof-of-concept study to predict the oxidative stress status in a healthy population using retrospective cohort data from Boramae medical center in Korea (n = 1328). To obtain binary performance measures, we selected healthy controls versus oxidative disease cases based on the "health space" statistical methodology. We then developed a machine learning algorithm for discrimination of oxidative stress status using least absolute shrinkage and selection operator (LASSO)/elastic net regression with 10-fold cross-validation. A proposed fine-tune model included 16 features out of the full spectrum of diverse and complex data. The predictive performance was externally evaluated by generating receiver operating characteristic curves with area under the curve of 0.949 (CI 0.925 to 0.974), sensitivity of 0.923 (CI 0.879 to 0.967), and specificity of 0.855 (CI 0.795 to 0.915). Moreover, the discrimination power was confirmed by applying the proposed diagnostic model to the full dataset consisting of subjects with various degrees of oxidative stress. The results provide a feasible approach for stratifying the oxidative stress risks in the healthy population and selecting appropriate strategies for individual subjects toward implementing data-driven precision nutrition.

A Novel Personalized Systems Nutrition Program Improves Dietary Patterns, Lifestyle Behaviors and Health-Related Outcomes: Results from the Habit Study.

Personalized nutrition may be more effective in changing lifestyle behaviors compared to population-based guidelines. This single-arm exploratory study evaluated the impact of a 10-week personalized systems nutrition (PSN) program on lifestyle behavior and health outcomes. Healthy men and women (n = 82) completed the trial. Individuals were grouped into seven diet types, for which phenotypic, genotypic and behavioral data were used to generate personalized recommendations. Behavior change guidance was also provided. The intervention reduced the intake of calories (-256.2 kcal; p < 0.0001), carbohydrates (-22.1 g; p < 0.0039), sugar (-13.0 g; p < 0.0001), total fat (-17.3 g; p < 0.0001), saturated fat (-5.9 g; p = 0.0003) and PUFA (-2.5 g; p = 0.0065). Additionally, BMI (-0.6 kg/m2; p < 0.0001), body fat (-1.2%; p = 0.0192) and hip circumference (-5.8 cm; p < 0.0001) were decreased after the intervention. In the subgroup with the lowest phenotypic flexibility, a measure of the body's ability to adapt to environmental stressors, LDL (-0.44 mmol/L; p = 0.002) and total cholesterol (-0.49 mmol/L; p < 0.0001) were reduced after the intervention. This study shows that a PSN program in a workforce improves lifestyle habits and reduces body weight, BMI and other health-related outcomes. Health improvement was most pronounced in the compromised phenotypic flexibility subgroup, which indicates that a PSN program may be effective in targeting behavior change in health-compromised target groups.

Evaluation of Food-Intake Behavior in a Healthy Population: Personalized vs. One-Size-Fits-All.

In public health initiatives, generic nutrition advice (GNA) from national guidelines has a limited effect on food-intake improvement. Personalized nutrition advice (PNA) may enable dietary behavior change. A monocentric, randomized, parallel, controlled clinical trial was performed in males (n = 55) and females (n = 100) aged 25 to 70 years. Participants were allocated to control, GNA or PNA groups. The PNA group consisted of automatically generated dietary advice based on personal metabolic health parameters, dietary intake, anthropometric and hemodynamic measures, gender and age. Participants who received PNA (n = 51) improved their nutritional intake status for fruits P (p < 0.0001), whole grains (p = 0.008), unsalted nuts (p < 0.0001), fish (p = 0.0003), sugar-sweetened beverages (p = 0.005), added salt (p = 0.003) and less unhealthy choices (p = 0.002), whereas no improvements were observed in the control and GNA group. PNA participants were encouraged to set a goal for one or multiple food categories. Goal-setting led to greater improvement of food categories within the PNA group including; unsalted nuts (p < 0.0001), fruits (p = 0.0001), whole grains (p = 0.005), fish (p = 0.0001), dairy (p = 0.007), vegetables (p = 0.01) and unhealthy choices (p = 0.02). In a healthy population, participants receiving PNA changed their food-intake behavior more favorably than participants receiving GNA or no advice. When personal goals were set, nutritional behavior was more prone to change.

Associations between Circulating Lipids and Fat-Soluble Vitamins and Carotenoids in Healthy Overweight and Obese Men.

Inconsistent associations between lipids and circulating markers of fat-soluble vitamin and carotenoid status have been reported. The aim of this hypothesis-generating study was to examine the contribution of the LC-MS-based lipidome, characterized by lipid class, carbon count, and the number of unsaturated bonds, to the interindividual variability in circulating concentrations of retinol, carotenoids, 25-hydroxyvitamin D3, α-tocopherol, γ-tocopherol, and phylloquinone in 35 overweight and obese, but healthy men. A sparse partial least-squares method was used to accomplish this aim. Highly abundant phospholipids and triglycerides (TGs) contributed to the interindividual variability in phylloquinone, α-tocopherol, and γ-tocopherol. Interindividual variability in lycopene concentrations was driven by concentrations of low-abundant TG. 25-Hydroxyvitamin D3, retinol, and the other carotenoids were not influenced by lipids. Except for lycopene, evaluation of lipids beyond class does not appear to further explain the interindividual variability in circulating concentrations of fat-soluble vitamins and carotenoids.

Network-Based Selection of Candidate Markers and Assays to Assess the Impact of Oral Immune Interventions on Gut Functions.

To assess the safety and efficacy of oral immune interventions, it is important and required by regulation to assess the impact of those interventions not only on the immune system, but also on other organs such as the gut as the porte d'entrée. Despite clear indications that the immune system interacts with several physiological functions of the gut, it is still unknown which pathways and molecules are crucial to assessing the impact of nutritional immune interventions on gut functioning. Here we used a network-based systems biology approach to clarify the molecular relationships between immune system and gut functioning and to identify crucial biomarkers to assess effects on gut functions upon nutritional immune interventions. First, the different gut functionalities were categorized based on literature and EFSA guidance documents. Moreover, an overview of the current assays and methods to measure gut function was generated. Secondly, gut-function related biological processes and adverse events were selected and subsequently linked to the physiological functions of the GI tract. Thirdly, database terms and annotations from the Gene ontology database and the Comparative Toxicogenomics Database (CTD) related to the previously selected gut-function related processes were selected. Next, database terms and annotations were used to identify the pathways and genes involved in those gut functionalities. In parallel, information from CTD was used to identify immune disease related genes. The resulting lists of both gut and immune function genes showed an overlap of 753 genes out of 1,296 gut-function related genes indicating the close gut-immune relationship. Using bioinformatics enrichment tools DAVID and Panther, the identified gut-immune markers were predicted to be involved in motility, barrier function, the digestion and absorption of vitamins and fat, regulation of the digestive system and gastric acid, and protection from injurious or allergenic material. Concluding, here we provide a promising systems biology approach to identify genes that help to clarify the relationships between immune system and gut functioning, with the aim to identify candidate biomarkers to monitor nutritional immune intervention assays for safety and efficacy in the general population. This knowledge helps to optimize future study designs to predict effects of nutritional immune intervention on gut functionalities.

The influence of treatment in alpine and moderate maritime climate on the composition of the skin microbiome in patients with difficult to treat atopic dermatitis.

BACKGROUND: The skin microbiome, characterized by an overgrowth of Staphylococcus aureus, plays an important role in the pathogenesis of atopic dermatitis (AD). Multidisciplinary treatment in alpine climate is known for its positive effect on disease severity in children with AD and can result in a different immune response compared with moderate maritime climate. However, the effect on the composition of the skin microbiome in AD is unknown. OBJECTIVE: To determine the effect of treatment in alpine climate and moderate maritime climate on the microbiome for lesional and non-lesional skin in children with difficult to treat AD. RESULTS: Alpine climate treatment led to a significant change in the microbiota on lesional skin, whereas no significant change was found after moderate maritime climate. On both lesional and non-lesional skin, we observed a significant increase in Shannon diversity and a significant decrease in both Staphylococcus abundance and S aureus load after alpine climate treatment. The decrease in S aureus was significantly larger on lesional skin following alpine climate treatment compared with moderate maritime climate treatment. Staphylococcus epidermidis load was stable over time. CONCLUSIONS AND CLINICAL RELEVANCE: Alpine climate treatment leads to significant changes in the composition of the skin microbiome in children with AD, mainly caused by a reduction in the Staphylococcus genus. This study shows new perspectives in the potential mode of action for therapies in AD.

Child development, growth and microbiota: follow-up of a randomized education trial in Uganda.

BACKGROUND: Undernutrition impairs child development outcomes and growth. In this follow-up study of an open cluster-randomized intervention trial we examined the effects of an education package delivered to mothers in rural Uganda on their children's development, growth and gut microbiota at 36 months of age. METHODS: The parental trial included 511 mother-child pairs recruited when the children were 6-8 months. In that trial, a nutrition, stimulation and hygiene education was delivered to mothers in the intervention group while the control group received routine health care. A follow-up sample of 155 pairs (intervention n = 77, control n = 78) were re-enrolled when the children were 24 months. Developmental outcomes were assessed with the Bayley Scales of Infant and Toddler Development (BSID-III) composite scores for cognitive (primary endpoint), language and motor development. Development outcomes were also evaluated using the Ages and Stages Questionnaire (ASQ) and the Mullen Scales of Early Learning (MSEL). Other outcomes included growth and gut microbiota composition. RESULTS: The demographic characteristics were not different (P > 0.05) between the intervention and control groups and similar to those of the parental study. The intervention group had higher BSID-III scores than controls, with mean difference 10.13 (95% confidence interval (CI): 3.31-17.05, P = 0.002); 7.59 (1.62-13.66, P = 0.01); 9.00 (2.92-15.40, P = 0.005), for cognitive, language and motor composite scores, respectively. An improvement in the intervention compared to the control group was obtained for both the ASQ and the MSEL scores. The mean difference in height-for-age z-score was higher in the intervention compared to the control group: 0.50 (0.25-0.75, P = 0.0001). Gut microbiota composition did not differ significantly between the two study groups. CONCLUSIONS: The maternal education intervention had positive effects on child development and growth at three years, but did not alter gut microbiota composition. This intervention may be applicable in other low-resource settings. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT02098031.

A network-based approach for identifying suitable biomarkers for oral immunotherapy of food allergy.

BACKGROUND: Oral immunotherapy (OIT) is a promising therapeutic approach to treat food allergic patients. However, concerns with regards to safety and long-term efficacy of OIT remain. There is a need to identify biomarkers that predict, monitor and/or evaluate the effects of OIT. Here we present a method to select candidate biomarkers for efficacy and safety assessment of OIT using the computational approaches Bayesian networks (BN) and Topological Data Analysis (TDA). RESULTS: Data were used from fructo-oligosaccharide diet-supported OIT experiments performed in 3 independent cow's milk allergy (CMA) and 2 independent peanut allergy (PNA) experiments in mice. Bioinformatical approaches were used to understand the data structure. The BN predicted the efficacy of OIT in the CMA with 86% and indicated a clear effect of scFOS/lcFOS on allergy parameters. For the PNA model, this BN (trained on CMA data) predicted an efficacy of OIT with 76% accuracy and shows similar effects of the allergen, treatment and diet as compared to the CMA model. The TDA identified clusters of biomarkers closely linked to biologically relevant clinical symptoms and also unrelated and redundant parameters within the network. CONCLUSIONS: Here we provide a promising application of computational approaches to a) compare mechanistic features of two different food allergies during OIT b) determine the biological relevance of candidate biomarkers c) generate new hypotheses to explain why CMA has a different disease pattern than PNA and d) select relevant biomarkers for future studies.

Dose-dependent impact of oxytetracycline on the veal calf microbiome and resistome.

BACKGROUND: Antibiotic therapy is commonly used in animal agriculture. Antibiotics excreted by the animals can contaminate farming environments, resulting in long term exposure of animals to sub-inhibitory levels of antibiotics. Little is known on the effect of this exposure on antibiotic resistance. In this study, we aimed to investigate the long term effects of sub-inhibitory levels of antibiotics on the gut microbiota composition and resistome of veal calves in vivo. Forty-two veal calves were randomly assigned to three groups. The first group (OTC-high) received therapeutic oral dosages of 1 g oxytetracycline (OTC), twice per day, during 5 days. The second group (OTC-low) received an oral dose of OTC of 100-200 µg per day during 7 weeks, mimicking animal exposure to environmental contamination. The third group (CTR) did not receive OTC, serving as unexposed control. Antibiotic residue levels were determined over time. The temporal effects on the gut microbiota and antibiotic resistance gene abundance was analysed by metagenomic sequencing. RESULTS: In the therapeutic group, OTC levels exceeded MIC values. The low group remained at sub-inhibitory levels. The control group did not reach any significant OTC levels. 16S rRNA gene-based analysis revealed significant changes in the calf gut microbiota. Time-related changes accounted for most of the variation in the sequence data. Therapeutic application of OTC had transient effect, significantly impacting gut microbiota composition between day 0 and day 2. By metagenomic sequence analysis we identified six antibiotic resistance genes representing three gene classes (tetM, floR and mel) that differed in relative abundance between any of the intervention groups and the control. qPCR was used to validate observations made by metagenomic sequencing, revealing a peak of tetM abundance at day 28-35 in the OTC-high group. No increase in resistance genes abundance was seen in the OTC-low group. CONCLUSIONS: Under the conditions tested, sub-therapeutic administration of OTC did not result in increased tetM resistance levels as observed in the therapeutic group.

The Impact of Maltitol-Sweetened Chewing Gum on the Dental Plaque Biofilm Microbiota Composition.

Background: The oral cavity harbors a complex microbial ecosystem, intimately related to oral health and disease. The use of polyol-sweetened gum is believed to benefit oral health through stimulation of salivary flow and impacting oral pathogenic bacteria. Maltitol is often used as sweetener in food products. This study aimed to establish the in vivo effects of frequent consumption of maltitol-sweetened chewing gum on the dental plaque microbiota in healthy volunteers and to establish the cellular and molecular effects by in vitro cultivation and transcriptional analysis. Results: An intervention study was performed in 153 volunteers, randomly assigned to three groups (www.trialregister.nl; NTR4165). One group was requested to use maltitol gum five times daily, one group used gum-base, and the third group did not use chewing gum. At day 0 and day 28, 24 h-accumulated supragingival plaque was collected at the lingual sites of the lower jaw and the buccal sites of the upper jaw and analyzed by 16S ribosomal rRNA gene sequencing. At day 42, 2 weeks after completion of the study, lower-jaw samples were collected and analyzed. The upper buccal plaque microbiota composition had lower bacterial levels and higher relative abundances of (facultative) aerobic species compared to the lower lingual sites. There was no difference in bacterial community structure between any of the three study groups (PERMANOVA). Significant lower abundance of several bacterial phylotypes was found in maltitol gum group compared to the gum-base group, including Actinomyces massiliensis HOT 852 and Lautropia mirabilis HOT 022. Cultivation studies confirmed growth inhibition of A. massiliensis and A. johnsonii by maltitol at levels of 1% and higher. Transcriptome analysis of A. massiliensis revealed that exposure to maltitol resulted in changes in the expression of genes linked to osmoregulation, biofilm formation, and central carbon metabolism. Conclusion: The results showed that chewing itself only marginally impacted the plaque microbiota composition. Use of maltitol-sweetened gum lowered abundance of several bacterial species. Importantly, the species impacted play a key role in the early formation of dental biofilms. Further studies are required to establish if frequent use of maltitol gum impacts early dental-plaque biofilm development.

Uncovering a Predictive Molecular Signature for the Onset of NASH-Related Fibrosis in a Translational NASH Mouse Model.

BACKGROUND & AIMS: The incidence of nonalcoholic steatohepatitis (NASH) is increasing. The pathophysiological mechanisms of NASH and the sequence of events leading to hepatic fibrosis are incompletely understood. The aim of this study was to gain insight into the dynamics of key molecular processes involved in NASH and to rank early markers for hepatic fibrosis. METHODS: A time-course study in low-density lipoprotein-receptor knockout. Leiden mice on a high-fat diet was performed to identify the temporal dynamics of key processes contributing to NASH and fibrosis. An integrative systems biology approach was used to elucidate candidate markers linked to the active fibrosis process by combining transcriptomics, dynamic proteomics, and histopathology. The translational value of these findings were confirmed using human NASH data sets. RESULTS: High-fat-diet feeding resulted in obesity, hyperlipidemia, insulin resistance, and NASH with fibrosis in a time-dependent manner. Temporal dynamics of key molecular processes involved in the development of NASH were identified, including lipid metabolism, inflammation, oxidative stress, and fibrosis. A data-integrative approach enabled identification of the active fibrotic process preceding histopathologic detection using a novel molecular fibrosis signature. Human studies were used to identify overlap of genes and processes and to perform a network biology-based prioritization to rank top candidate markers representing the early manifestation of fibrosis. CONCLUSIONS: An early predictive molecular signature was identified that marked the active profibrotic process before histopathologic fibrosis becomes manifest. Early detection of the onset of NASH and fibrosis enables identification of novel blood-based biomarkers to stratify patients at risk, development of new therapeutics, and help shorten (pre)clinical experimental time frames.