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International audience; Studies indicate that the intestinal microbiota influences general metabolic processes in humans, thereby modulating the risk of chronic diseases such as type 2 diabetes, allergy, cardiovascular disease, and colorectal cancer (CRC). Dietary factors are also directly related to chronic disease risk, and they affect the composition and function of the gut microbiota. Still, detailed knowledge on the relation between diet, the microbiota, and chronic disease risk is limited. The overarching aim of the HDHL-INTIMIC (INtesTInal MICrobiomics) knowledge platform is to foster studies on the microbiota, nutrition, and health by assembling available knowledge of the microbiota and of the other aspects (e.g., food science and metabolomics) that are relevant in the context of microbiome research. The goal is to make this information findable, accessible, interoperable, and reusable (FAIR) to the scientific community, and to share information with the various stakeholders. Through these efforts a network of transnational and multidisciplinary collaboration has emerged, which has contributed to further develop and increase the impact of microbiome research in human health. The roles of microbiota in early infancy, during ageing, and in subclinical and clinically manifested disease are identified as urgent areas of research in this knowledge platform.

Whether the gut microbiome in obesity is characterized by lower diversity and altered composition at the phylum or genus level may be more accurately investigated using high-throughput sequencing technologies. We conducted a systematic review in PubMed and Embase including 32 cross-sectional studies assessing the gut microbiome composition by high-throughput sequencing in obese and non-obese adults. A significantly lower alpha diversity (Shannon index) in obese versus non-obese adults was observed in nine out of 22 studies, and meta-analysis of seven studies revealed a non-significant mean difference (−0.06, 95% CI −0.24, 0.12, I2 = 81%). At the phylum level, significantly more Firmicutes and fewer Bacteroidetes in obese versus non-obese adults were observed in six out of seventeen, and in four out of eighteen studies, respectively. Meta-analyses of six studies revealed significantly higher Firmicutes (5.50, 95% 0.27, 10.73, I2 = 81%) and non-significantly lower Bacteroidetes (−4.79, 95% CI −10.77, 1.20, I2 = 86%). At the genus level, lower relative proportions of Bifidobacterium and Eggerthella and higher Acidaminococcus, Anaerococcus, Catenibacterium, Dialister, Dorea, Escherichia-Shigella, Eubacterium, Fusobacterium, Megasphera, Prevotella, Roseburia, Streptococcus, and Sutterella were found in obese versus non-obese adults. Although a proportion of studies found lower diversity and differences in gut microbiome composition in obese versus non-obese adults, the observed heterogeneity across studies precludes clear answers.

Within the last two decades tremendous efforts in biomedicine have been undertaken to understand the interplay of commensal bacteria living in and on our human body with our own human physiology. It became clear that (1) a high diversity especially of the microbial communities in the gut are important to preserve health and that (2) certain bacteria via nutrition-microbe-host metabolic axes are beneficially affecting various functions of the host, including metabolic control, energy balance and immune function. While a large set of evidence indicate a special role for small chain fatty acids (SCFA) in that context, recently also metabolites of amino acids (e.g., tryptophan and arginine) moved into scientific attention. Of interest, microbiome alterations are not only important in nutrition associated diseases like obesity and diabetes, but also in many chronic inflammatory, oncological and neurological abnormalities. From a clinician’s point of view, it should be mentioned, that the microbiome is not only interesting to develop novel therapies, but also as a modifiable factor to improve efficiency of modern pharmaceutics, e.g., immune-therapeutics in oncology. However, so far, most data rely on animal experiments or human association studies, whereas controlled clinical intervention studies are spare. Hence, the translation of the knowledge of the last decades into clinical routine will be the challenge of microbiome based biomedical research for the next years. This review aims to provide examples for future clinical applications in various entities and to suggest bacterial species and/or microbial effector molecules as potential targets for intervention studies.

BACKGROUND: Associations between increased dietary fat and decreased carbohydrate intake with circulating HDL and non-HDL cholesterol have not been conclusively determined. OBJECTIVE: We assessed these relations in 8 European observational human studies participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) using harmonized data. METHODS: Dietary macronutrient intake was recorded using study-specific dietary assessment tools. Main outcome measures were lipoprotein cholesterol concentrations: HDL cholesterol (mg/dL) and non-HDL cholesterol (mg/dL). A cross-sectional analysis on 5919 participants (54% female) aged 13-80 y was undertaken using the statistical platform DataSHIELD that allows remote/federated nondisclosive analysis of individual-level data. Generalized linear models (GLM) were fitted to assess associations between replacing 5% of energy from carbohydrates with equivalent energy from total fats, SFAs, MUFAs, or PUFAs with circulating HDL cholesterol and non-HDL cholesterol. GLM were adjusted for study source, age, sex, smoking status, alcohol intake and BMI. RESULTS: The replacement of 5% of energy from carbohydrates with total fats or MUFAs was statistically significantly associated with 0.67mg/dL (95% CI: 0.40, 0.94) or 0.99mg/dL (95% CI: 0.37, 1.60) higher HDL cholesterol, respectively, but not with non-HDL cholesterol concentrations. The replacement of 5% of energy from carbohydrates with SFAs or PUFAs was not associated with HDL cholesterol, but SFAs were statistically significantly associated with 1.94mg/dL (95% CI: 0.08, 3.79) higher non-HDL cholesterol, and PUFAs with -3.91mg/dL (95% CI: -6.98, -0.84) lower non-HDL cholesterol concentrations. A statistically significant interaction by sex for the association of replacing carbohydrates with MUFAs and non-HDL cholesterol was observed, showing a statistically significant inverse association in males and no statistically significant association in females. We observed no statistically significant interaction by age. CONCLUSIONS: The replacement of dietary carbohydrates with fats had favorable effects on lipoprotein cholesterol concentrations in European adolescents and adults when fats were consumed as MUFAs or PUFAs but not as SFAs.

The phenomenon of burnout is a complex issue, which despite major efforts from researchers and organizations remains hard to prevent. The current literature highlights an increasing global prevalence of employees that are dealing with burnout. What has been largely missing is a more systemic, dynamic, and personal perspective on the interactions of the key determinants of burnout. Burnout can be seen as the outcome of a complex system involving feedback loops between individual mental models, individual behavior, and external social influences. Understanding the feedback loops involved may enable employees and organizations to intervene in burnout trajectories early and effectively. System dynamics (SD) modeling is a methodology that can describe the structure and behavior of a complex system. The current paper describes the development of an SD model of burnout. First, an expert- and literature-informed causal loop diagram (CLD) of burnout is developed. Then, a novel approach is developed to collect personal retrospective scenario data. Finally, the CLD and data are translated into a quantitative SD model. The potential of the SD model is illustrated by simulating the behavior of three realistic personas during the onset of and recovery from burnout. The process of development of an SD model of burnout is presented and the strengths and limitations of the approach are discussed.

Background: There has been limited evidence about whether genotype-tailored advice provides extra benefits in reducing obesityrelated traits compared with the benefits of conventional one-size-fitsall advice. Objective: We determined whether the disclosure of information on fat-mass and obesity-associated (FTO) genotype risk had a greater effect on a reduction of obesity-related traits in risk carriers than in nonrisk carriers across different levels of personalized nutrition. Design: A total of 683 participants (women: 51%; age range: 18'73 y) from the Food4Me randomized controlled trial were included in this analysis. Participants were randomly assigned to 4 intervention arms as follows: level 0, control group; level 1, dietary group; level 2, phenotype group; and level 3, genetic group. FTO (single nucleotide polymorphism rs9939609) was genotyped at baseline in all participants, but only subjects who were randomly assigned to level 3 were informed about their genotypes. Level 3 participants were stratified into risk carriers (AA/AT) and nonrisk carriers (TT) of the FTO gene for analyses. Height, weight, and waist circumference (WC) were self-measured and reported at baseline and months 3 and 6. Results: Changes in adiposity markers were greater in participants who were informed that they carried the FTO risk allele (level 3 AT/AA carriers) than in the nonpersonalized group (level 0) but not in the other personalized groups (level 1 and 2). Mean reductions in weight andWC at month 6 were greater for FTO risk carriers than for noncarriers in the level 3 group [-2.28 kg (95% CI: -3.06, -1.48 kg) compared with -1.99 kg (-2.19, -0.19 kg), respectively (P = 0.037); and -4.34 cm(-5.63, -3.08 cm) compared with -1.99 cm (-4.04, -0.05 cm), respectively, (P = 0.048)]. Conclusions: There are greater body weight and WC reductions in risk carriers than in nonrisk carriers of the FTO gene. This trial was registered at clinicaltrials.gov as NCT01530139. © 2017 American Society for Nutrition.

Robust recommendations for healthy diets and nutrition require careful synthesis of available evidence. Given the increasing volume of research articles generated, the retrieval and synthesis of evidence are increasingly becoming laborious and time-consuming. Information technology could help to reduce workload for humans. To guide supervised learning however, human identification of key study characteristics is necessary. Reporting guidelines recommend that authors include essential content in articles and could generate manually labeled training data for automated evidence retrieval and synthesis. Here, we present a semiautomated approach to annotate, link, and track the content of nutrition research manuscripts. We used the STROBE extension for nutritional epidemiology (STROBE-nut) reporting guidelines to manually annotate a sample of 15 articles and converted the semantic information into linked data in a Neo4j graph database through an automated process. Six summary statistics were computed to estimate the reporting completeness of the articles. The content structure, presence of essential study characteristics as well as the reporting completeness of the articles are visualized automatically from the graph database. The archived linked data are interoperable through their annotations and relations. A graph database with linked data on essential study characteristics can enable Natural Language Processing in nutrition. Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

The gastro-intestinal microbiome has become the subject of intensive research, which is beginning to elucidate its roles in human health. It is becoming increasingly recognised that gut microbiota plays a part in regulating human immune homeostasis and metabolism, which gives rise to novel opportunities for preventative and treatment strategies. The key challenge in this field is the ability to define causality in the relationship between nutrition, microbiota and host health. In this commentary we argue for an increased focus on cause-and-effect relationships within studies that relate to the human microbiome in health and predispositions to disease. With the right experimental models, data accessibility infrastructure and advanced machine learning tools, causal relationships among components of complex host-microbiome systems can be elucidated.

Scope Several studies have examined the whole‐genome gene expression response in blood cells to high‐fat challenges with differing results. The study aims to identify consistently up‐ or downregulated genes and pathways in response to a high‐fat challenge using several integration methods. Methods and results Three studies measuring the gene expression response to a high‐fat challenge in white blood cells are evaluated for common trends using several integration methods. Overlap in differentially expressed genes between separate studies is examined, p‐values of each separate study are combined, and data are analyzed as one merged dataset. Differentially expressed genes and pathways are compared between these methods. Selecting genes differentially expressed in the three separate studies result in 67 differentially expressed genes, primarily involved in circadian pathways. Using the Fishers p‐value method and a merged dataset analysis, changes in 1097 and 1182 genes, respectively, are observed. The upregulated genes upon a high‐fat challenge are related to inflammation, whereas downregulated genes are related to unfolded protein response, protein processing, cholesterol biosynthesis, and translation. Conclusion A general gene expression response to a high‐fat challenge is identified. Compared to separate analyses, integrated analysis provides added value for the discovery of a consistent gene expression response., An integrated analysis on microarray datasets from several high‐fat challenge intervention studies is performed. Several integration methods to identify changes in PBMC gene expression upon a high‐fat challenge are used. This integrated analysis is shown to provide added value for the discovery of consistently differentially expressed genes and pathways compared to separate analysis of the studies.

Obesity, type 2 diabetes, and other metabolic disorders have a large impact on global health, especially in Western countries. An important hallmark of metabolic disorders is chronic low-grade inflammation. A key player in chronic low-grade inflammation is dysmetabolism, which is defined as the inability to keep homeostasis resulting in loss of lipid control, oxidative stress, inflammation, and insulin resistance. Although often not yet detectable in the circulation, chronic low-grade inflammation can be present in one or multiple organs. The response to a metabolic challenge containing lipids may magnify dysfunctionalities at the tissue level, causing an overflow of inflammatory markers into the circulation and hence allow detection of early low-grade inflammation. Here, we summarize the evidence of successful application of metabolic challenge tests in type 2 diabetes, metabolic syndrome, obesity, and unhealthy aging. We also review how metabolic challenge tests have been successfully applied to evaluate nutritional intervention effects, including an “anti-inflammatory” mixture, dark chocolate, whole grain wheat and overfeeding. Additionally, we elaborate on future strategies to (re)gain inflammatory flexibility. Through epigenetic and metabolic regulation, the inflammatory response may be trained by regular mild and metabolic triggers, which can be understood from the perspective of trained immunity, hormesis and pro-resolution. New strategies to optimize dynamics of inflammation may become available.

Aging is a biological process characterized by the progressive functional decline of many interrelated physiological systems. In particular, aging is associated with the development of a systemic state of low-grade chronic inflammation (inflammaging), and with progressive deterioration of metabolic function. Systems biology has helped in identifying the mediators and pathways involved in these phenomena, mainly through the application of high-throughput screening methods, valued for their molecular comprehensiveness. Nevertheless, inflammation and metabolic regulation are dynamical processes whose behavior must be understood at multiple levels of biological organization (molecular, cellular, organ, and system levels) and on multiple time scales. Mathematical modeling of such behavior, with incorporation of mechanistic knowledge on interactions between inflammatory and metabolic mediators, may help in devising nutritional interventions capable of preventing, or ameliorating, the age-associated functional decline of the corresponding systems. © 2014 The Authors.

This is the peer reviewed version of the following article: Carlos Celis-Morales, et al, ‘Physical activity attenuates the effect of the FTO genotype on obesity traits in European adults: The Food4Me study’, Obesity, Vol. 24 (4): 962-969, April 2016, which has been published in final form at DOI: https://doi.org/10.1002/oby.21422. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Objective: Aim is to predict successful weight loss by metabolic signatures at baseline and to identify which differences in metabolic status may underlie variations in weight loss success. Methods: In DiOGenes, a randomized, controlled trial, weight loss was induced using a low calorie diet (800 kcal) for 8-weeks. Men (N5236) and women (N5431) as well as groups with overweight/obesity and morbid obesity were studied separately. The relation between the metabolic status before weight loss and weight loss was assessed by stepwise regression on multiple datasets, including anthropometric parameters, NMR-based plasma metabolites, and LC-MS-based plasma lipid species. Results: Maximally, 57% of the variation in weight loss success can be predicted by baseline parameters. The most powerful predictive models were obtained in subjects with morbid obesity. In these models, the metabolites most predictive for weight loss were acetoacetate, triacylglycerols, phosphatidylcholines, specific amino acids, and creatine and creatinine. This metabolic profile suggests that high energy metabolism activity results in higher amounts of weight loss. Conclusions: Possible predictive (pre-diet) markers were found for amount of weight loss for specific subgroups.

Risk variants of fat mass and obesity-associated (FTO) gene have been associated with increased obesity. However, the evidence for associations between FTO genotype and macronutrient intake has not been reviewed systematically. Our aim was to evaluate the potential associations between FTO genotype and intakes of total energy, fat, carbohydrate and protein. We undertook a systematic literature search in OVID MEDLINE, Scopus, EMBASE and Cochrane of associations between macronutrient intake and FTO genotype in adults. Beta coefficients and confidence intervals (CIs) were used for per allele comparisons. Random-effect models assessed the pooled effect sizes. We identified 56 eligible studies reporting on 213,173 adults. For each copy of the FTO risk allele, individuals reported 6.46kcal day-1 (95% CI: 10.76, 2.16) lower total energy intake (P=0.003). Total fat (P=0.028) and protein (P=0.006), but not carbohydrate intakes, were higher in those carrying the FTO risk allele. After adjustment for body weight, total energy intakes remained significantly lower in individuals with the FTO risk genotype (P=0.028). The FTO risk allele is associated with a lower reported total energy intake and with altered patterns of macronutrient intake. Although significant, these differences are small and further research is needed to determine whether the associations are independent of dietary misreporting. © 2015 International Association for the Study of Obesity. Chemicals/CAS: alcohol, 64-17-5; protein, 67254-75-5

Agile introduction on ontologies, how to use them and contribute to ONS. (PDF 2119Â kb)

BACKGROUND: Joint data analysis from multiple nutrition studies may improve the ability to answer complex questions regarding the role of nutritional status and diet in health and disease. OBJECTIVE: The objective was to identify nutritional observational studies from partners participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) Consortium, as well as minimal requirements for joint data analysis. METHODS: A predefined template containing information on study design, exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measures, and sociodemographic and health status), main health-related outcomes, and laboratory measurements (traditional and omics biomarkers) was developed and circulated to those European research groups participating in the ENPADASI under the strategic research area of "diet-related chronic diseases." Information about raw data disposition and metadata sharing was requested. A set of minimal requirements was abstracted from the gathered information. RESULTS: Studies (12 cohort, 12 cross-sectional, and 2 case-control) were identified. Two studies recruited children only and the rest recruited adults. All studies included dietary intake data. Twenty studies collected blood samples. Data on traditional biomarkers were available for 20 studies, of which 17 measured lipoproteins, glucose, and insulin and 13 measured inflammatory biomarkers. Metabolomics, proteomics, and genomics or transcriptomics data were available in 5, 3, and 12 studies, respectively. Although the study authors were willing to share metadata, most refused, were hesitant, or had legal or ethical issues related to sharing raw data. Forty-one descriptors of minimal requirements for the study data were identified to facilitate data integration. CONCLUSIONS: Combining study data sets will enable sufficiently powered, refined investigations to increase the knowledge and understanding of the relation between food, nutrition, and human health. Furthermore, the minimal requirements for study data may encourage more efficient secondary usage of existing data and provide sufficient information for researchers to draft future multicenter research proposals in nutrition. ispartof: The Journal of Nutrition vol:148 issue:2 pages:285-297 ispartof: location:United States status: published

Nutrigenetic research examines the effects of inter-individual differences in genotype on responses to nutrients and other food components, in the context of health and of nutrient requirements. A practical application of nutrigenetics is the use of personal genetic information to guide recommendations for dietary choices that are more efficacious at the individual or genetic subgroup level relative to generic dietary advice. Nutrigenetics is unregulated, with no defined standards, beyond some commercially adopted codes of practice. Only a few official nutrition-related professional bodies have embraced the subject, and, consequently, there is a lack of educational resources or guidance for implementation of the outcomes of nutrigenetic research. To avoid misuse and to protect the public, personalised nutrigenetic advice and information should be based on clear evidence of validity grounded in a careful and defensible interpretation of outcomes from nutrigenetic research studies. Evidence requirements are clearly stated and assessed within the context of state-of-the-art 'evidence-based nutrition'. We have developed and present here a draft framework that can be used to assess the strength of the evidence for scientific validity of nutrigenetic knowledge and whether 'actionable'. In addition, we propose that this framework be used as the basis for developing transparent and scientifically sound advice to the public based on nutrigenetic tests. We feel that although this area is still in its infancy, minimal guidelines are required. Though these guidelines are based on semi-quantitative data, they should stimulate debate on their utility. This framework will be revised biennially, as knowledge on the subject increases. © 2017 The Author(s).

Pooled analysis of secondary data increases the power of research and enables scientific discovery in nutritional epidemiology. Information on study characteristics that determine data quality is needed to enable correct reuse and interpretation of data. This study aims to define essential quality characteristics for data from observational studies in nutrition. First, a literature review was performed to get an insight on existing instruments that assess the quality of cohort, case-control, and cross-sectional studies and dietary measurement. Second, 2 face-to-face workshops were organized to determine the study characteristics that affect data quality. Third, consensus on the data descriptors and controlled vocabulary was obtained. From 4884 papers retrieved, 26 relevant instruments, containing 164 characteristics for study design and 93 characteristics for measurements, were selected. The workshop and consensus process resulted in 10 descriptors allocated to "study design" and 22 to "measurement" domains. Data descriptors were organized as an ordinal scale of items to facilitate the identification, storage, and querying of nutrition data. Further integration of an Ontology for Nutrition Studies will facilitate interoperability of data repositories. © 2017 American Society for Nutrition.

Background: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. Methods: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. Results: Ontologies for &ldquo, food and nutrition&rdquo, (n = 37), &ldquo, disease and specific population&rdquo, (n = 100), &ldquo, data description&rdquo, (n = 21), &ldquo, research description&rdquo, (n = 35), and &ldquo, supplementary (meta) data description&rdquo, (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. Conclusion: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology.

The EURopean micronutrient RECommendations Aligned (EURRECA) Network of Excellence explored the process of setting micronutrient recommendations to address the variance in recommendations across Europe. Work centered upon the transparent assessment of nutritional requirements via a series of systematic literature reviews and meta-analyses. In addition, the necessity of assessing nutritional requirements and the policy context of setting micronutrient recommendations was investigated. Findings have been presented in a framework that covers nine activities clustered into four stages: stage one Defining the problem describes Activities 1 and 2: Identifying the nutrition-related health problem and Defining the process; stage two Monitoring and evaluating describes Activities 3 and 7: Establishing appropriate methods, and Nutrient intake and status of population groups; stage three Deriving dietary reference values describes Activities 4, 5, and 6: Collating sources of evidence, Appraisal of the evidence, and Integrating the evidence; stage four Using dietary reference values in policy making describes Activities 8 and 9: Identifying policy options, and Evaluating policy implementation. These activities provide guidance on how to resolve various issues when deriving micronutrient requirements and address the methodological and policy decisions, which may explain the current variation in recommendations across Europe. [Supplementary materials are available for this article. Go to the publisher's online edition of Critical Reviews in Food Science and Nutrition for the following free supplemental files: Additional text, tables, and figures.] This is the peer-reviewed version of the article: Dhonukshe-Rutten Rosalie, Bouwman Jildau, Brown Kerry A., Cavelaars Adrienne E., Collings Rachel, Grammatikaki Evangelia, de Groot Lisette, Gurinović Mirjana A., Harvey Linda, Hermoso Maria, Hurst Rachel, Kremer Bas, Ngo Joy, Novaković Romana, Raats Monique M., Rollin Fanny, Serra-Majem Lluis, Souverein Olga W., Timotijević Lada, van't Veer Pieter, "EURRECA-Evidence-Based Methodology for Deriving Micronutrient Recommendations" 53, no. 10 (2013):999-1040, [https://doi.org/10.1080/10408398.2012.749209]

Background: Optimal nutritional choices are linked with better health, but many current interventions to improve diet have limited effect. We tested the hypothesis that providing personalized nutrition (PN) advice based on information on individual diet and lifestyle, phenotype and/or genotype would promote larger, more appropriate, and sustained changes in dietary behaviour.\ud \ud Methods: Adults from seven European countries were recruited to an internet-delivered intervention (Food4Me) and randomized to: (i) conventional dietary advice (control) or to PN advice based on: (ii) individual baseline diet; (iii) individual baseline diet plus phenotype (anthropometry and blood biomarkers); or (iv) individual baseline diet plus phenotype plus genotype (five diet-responsive genetic variants). Outcomes were dietary intake, anthropometry and blood biomarkers measured at baseline and after 3 and 6 months’ intervention.\ud \ud Results: At baseline, mean age of participants was 39.8 years (range 18–79), 59% of participants were female and mean body mass index (BMI) was 25.5 kg/m2. From the enrolled participants, 1269 completed the study. Following a 6-month intervention, participants randomized to PN consumed less red meat [-5.48 g, (95% confidence interval:-10.8,-0.09), P = 0.046], salt [-0.65 g, (−1.1,-0.25), P = 0.002] and saturated fat [-1.14 % of energy, (−1.6,-0.67), P

Background: The apolipoprotein E (APOE) risk allele (e4) is associated with higher total cholesterol (TC), amplified response to saturated fatty acid (SFA) reduction, and increased cardiovascular disease. Although knowledge of gene risk may enhance dietary change, it is unclear whether e4 carriers would benefit from gene-based personalized nutrition (PN). Objectives: The aims of this study were to 1) investigate interactions between APOE genotype and habitual dietary fat intake and modulations of fat intake on metabolic outcomes; 2) determine whether gene-based PN results in greater dietary change than do standard dietary advice (level 0) and nongene-based PN (levels 1-2); and 3) assess the impact of knowledge of APOE risk (risk: E4+, nonrisk: E42) on dietary change after gene-based PN (level 3). Design: Individuals (n = 1466) recruited into the Food4Me pan- European PN dietary intervention study were randomly assigned to 4 treatment arms and genotyped for APOE (rs429358 and rs7412). Diet and dried blood spot TC and v-3 (n-3) index were determined at baseline and after a 6-mo intervention. Data were analyzed with the use of adjusted general linear models. Results: Significantly higher TC concentrations were observed in E4+ participants than in E42 (P , 0.05). Although there were no significant differences in APOE response to gene-based PN (E4+ compared with E42), both groups had a greater reduction in SFA (percentage of total energy) intake than at level 0 (mean 6 SD: E4+, 20.72% 6 0.35% compared with 21.95% 6 0.45%, P = 0.035; E42, 20.31% 6 0.20% compared with 21.68% 6 0.35%, P = 0.029). Gene-based PN was associated with a smaller reduction in SFA intake than in nongene-based PN (level 2) for E42 participants (21.68% 6 0.35% compared with 22.56% 6 0.27%, P = 0.025). Conclusions: The APOE e4 allele was associated with higher TC. Although gene-based PN targeted to APOE was more effective in reducing SFA intake than standard dietary advice, there was no difference between APOE "risk" and "nonrisk" groups. Furthermore, disclosure of APOE nonrisk may have weakened dietary response to PN. This trial was registered at clinicaltrials.gov as NCT01530139. Am J Clin Nutr 2016;104:827-36. © 2016 American Society for Nutrition.

Managing paleoscience data is highly challenging to the multiplicity of actors in play, types of sampling, analysis, post-analysis treatments, statistics etc. However, a well-structured curating of data would permit innovative developments based on data and/or sample re-use, such as meta-analysis or the development of new proxies on previously studied cores. In this paper, we will present two recent initiatives that allowed us tackling this objective at a French national level: the “National Cyber Core Repository” (NCCR) and the “LTER-France retro-observatory” (ROZA).NCCR was developed under the umbrella of the French National Center fo Coring and Drilling (C2FN) thanks to the national excellence equipment project CLIMCOR. It aims at gathering on a unique website the locations and metadata of any scientific coring/drilling performed by French teams or using French facilities, whatever the type of archive it is (lake/marine sediment; ice etc.). It uses international standard, notably IGSN (for samples), ORCID (for persons) and DOI (for campaigns). NCC follows the INSPIRE ISO 19115 standard in order to catalogue the data. For continental sediment, NCCR may be fed directly on the field through a specifically developed mobile application.Based on NCCR, further initiatives may be led. In particular, under the umbrella of LTER-France (Long Term Ecological Research), we developed ROZA in order to facilitate the re-use of data and samples. Here the idea is to capitalise the knowledge on a given lake from which several sediment cores can be taken through time. In that aim we selected at least one lake from each of the 13 areas composing the network LTER-France. To enter the database, a set of mandatory data must be provided under a pre-determined format. In that case, the insertion of ROZA within the network LTER will favor to use of paleodata by non-paleodata scientists, in particular ecologists.

The mammalian gastrointestinal tract (GIT) harbors microorganisms (the microbiota) of vast phylogentic, genomic, and metabolic diversity, and recent years have seen a rapid development in the techniques for studying these complex microbial ecosystems. It is increasingly apparent that the GIT microbiota plays an intricate role in host health and disease. Targeted strategies for modulating human health through the modification of the GIT microbiota, however, are developing and in their infancy. This perspective article discusses the rationale, benefits and limitations of using the GIT microbiota as a pharmacological and nutritional target in the treatment of various diseases and disorders linked to imbalances in our microbiota.

Recommended dietary allowances for micronutrients fluctuate noticeably within European Union countries. The Network of Excellence EURRECA (EURopean micronutrient RECommendations Aligned) aims at harmonising micronutrient intake recommendations through population groups. The lack of proper markers of status for some micronutrients limits progress in this area: metabolomics could help identifying such new markers. We developed an original metabolomic strategy in order to monitor the largest fraction of a list of >270 metabolites known to be influenced by the micronutrients of interest. To improve the coverage of these metabolites in plasma, a multi platform approach was performed using both liquid and gas chromatography coupled to mass spectrometry. A sample preparation protocol based on a three-step plasma fractionation has been set up, using both liquid and solid phase extractions. Four fractions were obtained containing respectively polar metabolites, neutral lipids, free fatty acids and polar lipids. Recoveries were determined using spiked plasma samples, and the advantages and drawbacks of the fractionation method compared to a commonly used single preparation step method were investigated in terms of metabolites detection and robustness. Fractionation improved coverage of the endogenous metabolome more than twice in terms of extracted features, allowing to identify 90 metabolites. © 2012 Springer Science+Business Media, LLC.

Intracellular accumulation of glycerol is essential for yeast cells to survive hyperosmotic stress. Upon hyperosmotic stress the gene expression of enzymes in the glycerol pathway is strongly induced. Recently, however, it was shown that this gene-expression response is not essential for survival of an osmotic shock [Mettetal JT et al. (2008) Science 319: 482-484 and Westfall PJ et al. (2008) Proc Natl Acad Sci 105: 12212-12217]. Instead, pure metabolic adaptation can rescue the yeast. The existence of two alternative mechanisms urged the question which of these mechanisms dominates time-dependent adaptation of wild-type yeast to osmotic stress under physiological conditions. The regulation of the glycerol pathway was analysed in aerobic, glucose-limited cultures upon addition of 1 M of sorbitol, leading to a hyperosmotic shock. In agreement with earlier studies, the mRNA levels of the glycerol-producing enzymes as well as their catalytic capacities increased. Qualitatively this induction followed a similar time course to the increase of the glycerol flux. However, a quantitative regulation analysis of the data revealed an initial regulation by metabolism alone. After only a few minutes gene expression came into play, but even after an hour, 80% of the increase in the glycerol flux was explained by metabolic changes in the cell, and 20% by induction of gene expression. This demonstrates that the novel metabolic mechanism is not just a secondary rescue mechanism, but the most important mechanism to regulate the glycerol flux under physiological conditions. Copyright (C) 2010 John Wiley & Sons, Ltd.

Awareness is growing that drug target validation should involve systems analysis of cellular networks. There is less appreciation, though, that the composition of networks may change in response to drugs. If the response is homeostatic (e.g. through upregulation of the target protein), this may neutralize the inhibitory effect. In this scenario the effect on cell growth and survival would be less than anticipated based on affinity of the drug for its target. Glycolysis is the sole free-energy source for the deadly parasite Trypanosoma brucei and is therefore a possible target pathway for anti-trypanosomal drugs. Plasma-membrane glucose transport exerts high control over trypanosome glycolysis and hence the transporter is a promising drug target. Here we show that at high inhibitor concentrations, inhibition of trypanosome glucose transport causes cell death. Most interestingly, sublethal concentrations initiate a domino effect in which network adaptations enhance inhibition. This happens via (i) metabolic control exerted by the target protein, (ii) decreases in mRNAs encoding the target protein and other proteins in the same pathway, and (iii) partial differentiation of the cells leading to (low) expression of immunogenic insect-stage coat proteins. We discuss how these 'anti-homeostatic' responses together may facilitate killing of parasites at an acceptable drug dosage.

In this study, the authors investigated how the glycolytic flux was regulated in time upon nitrogen starvation of cells with different growth histories. We have compared cells grown in glucose-limited chemostat cultures under respiratory conditions (low dilution rate of 0.1/h) to cells grown under respirofermentative conditions (high dilution rate of 0.35/h). The fermentative capacity was lower in cells grown under respiratory conditions than in cells grown under respirofermentative conditions, yet more resilient to prolonged nitrogen starvation. The time profiles revealed that the fermentative capacity even increased in cells grown under respiratory conditions during the first hours of nitrogen starvation. In cells grown under respirofermentative conditions the fermentative capacity decreased from the onset of nitrogen starvation. We have applied timedependent Regulation Analysis to follow the fermentative capacity during nitrogen starvation. In both experiments, diverse categories of regulation were found. However, in the cells grown under respiratory conditions regulation was predominantly metabolic, whereas in the cells grown under respirofermentative conditions hierarchical regulation was dominant. To study the metabolic regulation, concentrations of intracellular metabolites, including allosteric regulators, were measured. The obtained results can explain some aspects of the metabolic regulation, but not all. © The Institution of Engineering and Technology 2010.

Realistic quantitative models require data from many laboratories. Therefore, standardization of experimental systems and assay conditions is crucial. Moreover, standards should be representative of the in vivo conditions. However, most often, enzyme-kinetic parameters are measured under assay conditions that yield the maximum activity of each enzyme. In practice, this means that the kinetic parameters of different enzymes are measured in different buffers, at different pH values, with different ionic strengths, etc. In a joint effort of the Dutch Vertical Genomics Consortium, the European Yeast Systems Biology Network and the Standards for Reporting Enzymology Data Commission, we have developed a single assay medium for determining enzyme-kinetic parameters in yeast. The medium is as close as possible to the in vivo situation for the yeast Saccharomyces cerevisiae, and at the same time is experimentally feasible. The in vivo conditions were estimated for S. cerevisiae strain CEN.PK113-7D grown in aerobic glucose-limited chemostat cultures at an extracellular pH of 5.0 and a specific growth rate of 0.1 h(-1). The cytosolic pH and concentrations of calcium, sodium, potassium, phosphorus, sulfur and magnesium were determined. On the basis of these data and literature data, we propose a defined in vivo-like medium containing 300 mM potassium, 50 mM phosphate, 245 mM glutamate, 20 mM sodium, 2 mM free magnesium and 0.5 mM calcium, at a pH of 6.8. The V(max) values of the glycolytic and fermentative enzymes of S. cerevisiae were measured in the new medium. For some enzymes, the results deviated conspicuously from those of assays done under enzyme-specific, optimal conditions.

Time-dependent regulation analysis is a new methodology that allows us to unravel, both quantitatively and dynamically, how and when functional changes in the cell are brought about by the interplay of gene expression and metabolism. In this first experimental implementation, we dissect the initial and late response of baker's yeast upon a switch from glucose-limited growth to nitrogen starvation. During nitrogen starvation, unspecific bulk degradation of cytosolic proteins and small organelles (autophagy) occurs. If this is the primary cause of loss of glycolytic capacity, one would expect the cells to regulate their glycolytic capacity through decreasing simultaneously and proportionally the capacities of the enzymes in the first hour of nitrogen starvation. This should lead to regulation of the flux which is initially dominated by changes in the enzyme capacity. However, metabolic regulation is also known to act fast. To analyse the interplay between autophagy and metabolism, we examined the first 4 h of nitrogen starvation in detail using time-dependent regulation analysis. Some enzymes were initially regulated more by a breakdown of enzyme capacity and only later through metabolic regulation. However, other enzymes were regulated metabolically in the first hours and then shifted towards regulation via enzyme capacity. We conclude that even initial regulation is subtle and governed by different molecular levels.

Dietary intakes for the MTHFR risk, MTHFR non-risk and control groups at M0 and M3. Table S2. Dietary intakes by MTHFR risk and MTHFR non-risk participants who received folate-related goal (i.e. those who were told to increase their folate intake and those who were told to maintain their current folate intakes) compared with those who received generic healthy eating advice at M0 and M3. Table S3. Dietary intakes by MTHFR risk and MTHFR non-risk participants who were told to increase their folate intake compared with those who received generic healthy eating advice at M0 and M3. Table S4. Comparison of dietary intakes for the MTHFR risk, MTHFR non-risk and those who received personalised nutrition advice without genotype (levels 1 and 2) at M0 and M6. Table S5. Comparison of dietary intakes for the MTHFR risk, MTHFR non-risk and those who received personalised nutrition advice without genotype (levels 1 and 2) at M0 and M3. (DOCX 36 kb)

Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative ‘coordination of standards in metabolomics’ (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities’ participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.

Cells adapt to changes in their environment by the concerted action of many different regulatory mechanisms. Examples of such mechanisms are feedback inhibition by intermediates of metabolism, covalent modification of enzymes and changes in the abundance of mRNAs and proteins. These mechanisms act in parallel at different levels in the cellular hierarchy while regulating a single process. Existing hierarchical regulation analysis determines the relative importance of these mechanisms when the cell regulates a transition from one steady-state to another. Here, the analysis is extended to the regulation of time-dependent phenomena, for which two methods are introduced and illustrated with a kinetic model incorporating transcription and translation of metabolic enzymes. © The Institution of Engineering and Technology 2006.

Item does not contain fulltext Outgrowing axons in the developing nervous system secrete neurotransmitters and neuromodulatory substances, which is considered to stimulate synaptogenesis. However, some synapses develop independent of presynaptic secretion. To investigate the role of secretion in synapse formation and maintenance in vivo, we quantified synapses and their morphology in the neocortical marginal zone of munc18-1 deficient mice which lack both evoked and spontaneous secretion [Science 287 (2000) 864]. Histochemical analyses at embryonic day 18 (E18) showed that the overall organization of the neocortex and the number of cells were similar in mutants and controls. Western blot analysis revealed equal concentrations of pre- and post-synaptic marker proteins in mutants and controls and immunocytochemical analyses indicated that these markers were targeted to the neuropil of the synaptic layer in the mutant neocortex. Electron microscopy revealed that at E16 immature synapses had formed both in mutants and controls. These synapses had a similar synapse diameter, active zone length and contained similar amounts of synaptic vesicles, which were immunopositive for two synaptic vesicle markers. However, these synapses were three times less abundant in the mutant. Two days later, E18, synapses in the controls had more total and docked vesicles, but not in the mutant. Furthermore, synapses were now five times less abundant in the mutant. In both mutant and controls, synapse-like structures were observed with irregular shaped vesicles on both sides of the synaptic cleft. These 'multivesicular structures' were immuno-positive for synaptic vesicle markers and were four times more abundant in the mutant. We conclude that in the absence of presynaptic secretion immature synapses with a normal morphology form, but fewer in number. These secretion-deficient synapses might fail to mature and instead give rise to multivesicular structures. These two observations suggest that secretion of neurotransmitters and neuromodulatory substances is required for synapse maintenance, not for synaptogenesis. Multivesicular structures may develop out of unstable synapses. (C) 2004 IBRO. Published by Elsevier Ltd. All rights reserved.