Del i serien Woodhead Publishing Series in Food Science, Technology and Nutrition

Metabolomics as a Tool in Nutrition Research

Inbunden, Engelska, 2014

2 569 kr

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Metabolomics is a multidisciplinary science used to understand the ways in which nutrients from food are used in the body and how this can be optimised and targeted at specific nutritional needs. Metabolomics as a Tool in Nutrition Research provides a review of the uses of metabolomics in nutritional research. Chapters cover the most important aspects of the topic such as analysis techniques, bioinformatics and integration with other 'omic' sciences such as proteomics and genomics. The final chapters look at the impact of exercise on metabolomic profiles and future trends in metabolomics for nutrition research.

Produktinformation

Utgivningsdatum2014-12-08
Mått152 x 229 x 22 mm
Vikt530 g
FormatInbunden
SpråkEngelska
SerieWoodhead Publishing Series in Food Science, Technology and Nutrition
Antal sidor268
FörlagElsevier Science
ISBN9781782420842

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List of contributorsWoodhead Publishing Series in Food Science, Technology and NutritionPrefacePart One: Principles1. Challenges in nutritional metabolomics: from experimental design to interpretation of data setsAbstract1.1 Introduction1.2 The experimental design1.3 The analytical platform1.4 Extraction of data sets and statistical analyses1.5 Metabolite identification1.6 Biological interpretations1.7 Conclusion: do we need standardisation procedures and repositories?2. Metabolic profiling as a tool in nutritional research: key methodological issuesAbstract2.1 Introduction2.2 Key issues in nutritional research2.3 The role of genomics, proteomics, metabolomics, and metagenomics in nutritional research2.4 Applications of metabolomics in nutrition-related research2.5 The use of metabolomics to assess the effects of diet on health2.6 Methods for mapping dietary patterns2.7 Observational and interventional studies into the effects of diet and nutrition on health2.8 Analytical methods2.9 Issues in analysing samples3. Chemometrics methods for the analysis of genomics, transcriptomics, proteomics, metabolomics, and metagenomics datasetsAbstract3.1 Introduction3.2 Unsupervised and supervised pattern recognition methods3.3 Multivariate calibration methods for developing predictive models3.4 Statistical data integration methods3.5 Data integration: multiblock strategies3.6 Data integration: calibration transfer methods3.7 Data integration: multiway/multimodal analysis methods3.8 Data integration: correlation-based approaches3.9 Data integration: techniques for analysing different types of genomics datasets3.10 Statistical data integration of different sample types3.11 Statistical data integration of different molecular components in samples3.12 Modelling relationships between molecular components3.13 Conclusion and future trendsPart Two: Applications in nutrition research4. Application of lipidomics in nutrition researchAbstractAcknowledgement4.1 Introduction4.2 Lipids4.3 Lipidomics4.4 Lipidomics in nutrition research4.5 Conclusion and future trends5. Analysing human metabolic networks using metabolomics: understanding the impact of diet on healthAbstractAcknowledgements5.1 Introduction5.2 Metabolic network reconstruction5.3 Human metabolic networks5.4 Linking metabolomics data and metabolic network elements5.5 Metabolism modelling, from pathways to network5.6 Subnetwork extraction between identified metabolites5.7 Conclusion and future directions6. Using metabolomics to analyse the role of gut microbiota in nutrition and diseaseAbstract6.1 Introduction: gut microbiota and human health6.2 Metagenomics of gut microbiota6.3 Metabolomics: uncovering complex host–microbe interactions6.4 The marriage of metagenomics and metabolomics: microbiome–metabolome interactions6.5 Future perspectives: personalised nutrition7. Metabotyping: moving towards personalised nutritionAbstract7.1 Introduction7.2 The concept of the metabotype7.3 Examples of metabotyping with a focus on nutrition7.4 Extension of metabotypes to include markers of dietary origin7.5 Conclusion and future trends7.6 Sources of further information and advice8. Using metabolomics to identify biomarkers for metabolic diseases: analytical methods and applicationsAbstract8.1 Introduction8.2 Using metabolomics to understand the relationship between nutrition and chronic metabolic diseases8.3 Cohort studies and biomarker identification8.4 Isolating in situ biomarkers8.5 Conclusions and future trends9. Using metabolomics to evaluate food intake: applications in nutritional epidemiologyAbstract9.1 Introduction9.2 Biomarkers as a complementary approach to questionnaires9.3 Definition of the food metabolome9.4 Metabolomics as a tool for dietary biomarker discovery9.5 Dietary patterns and metabolomic profiles: potential use of nutritypes9.6 Validation of putative biomarkers9.7 The future of metabolomics in dietary assessment9.8 Conclusion10. Metabolomics and nutritional challenge tests: what can we learn?Abstract10.1 Introduction10.2 Application of metabolomics to challenge tests10.3 Conclusion and future trends11. Using metabolomics to describe food in detailAbstract11.1 Introduction11.2 Using metabolomics to assess the effects of genetic selection and modification11.3 Using metabolomics to assess the effects of organic versus conventional farming11.4 Using metabolomics to identify the geographical origin of food products11.5 Using metabolomics to assess the effects of rearing conditions on the quality of meat, eggs, and fish11.6 Using metabolomics to assess the effects of processing on food quality11.7 Using metabolomics to assess the effects of digestion on nutrient intake from particular foods11.8 ConclusionAppendix: abbreviations12. Future perspectives for metabolomics in nutrition research: a nutritionist’s viewAbstract12.1 Introduction12.2 Metabolites identification and biological relevance12.3 In vivo metabolomics12.4 ConclusionIndex