Metabolomics as a tool in nutrition research / edited by J.-L. Sébédio and L. Brennan.

Format:

Book

Contributor:

Sebedio, J.-L., editor.

Brennan, L. (Lance), editor.

Series:

Woodhead Publishing in food science, technology, and nutrition ; Number 266.

Woodhead Publishing Series in Food Science, Technology and Nutrition ; Number 266

Language:

English

Subjects (All):

Metabolism.

Nutrition--Research.

Nutrition.

Physical Description:

1 online resource (242 p.)

Edition:

First edition.

Place of Publication:

Cambridge, England : Woodhead Publishing, 2015.

Language Note:

English

System Details:

text file

Summary:

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.

Contents:

Front Cover

Metabolomics as a Tool in Nutrition Research

Copyright

Contents

List of contributors

Woodhead Publishing Series in Food Science, Technology and Nutrition

Preface

Part One: Principles

Chapter 1: Challenges in nutritional metabolomics: from experimental design to interpretation of data sets

1.1. Introduction

1.2. The experimental design

1.3. The analytical platform

1.4. Extraction of data sets and statistical analyses

1.5. Metabolite identification

1.6. Biological interpretations

1.7. Conclusion: do we need standardisation procedures and repositories?

References

Chapter 2: Metabolic profiling as a tool in nutritional research

2.1. Introduction

2.2. Key issues in nutritional research

2.3. The role of genomics, proteomics, metabolomics, and metagenomics in nutritional research

2.4. Applications of metabolomics in nutrition-related research

2.5. The use of metabolomics to assess the effects of diet on health

2.5.1. Natural products

2.5.2. Wheat and fibre

2.5.3. Meat and fish

2.5.4. Milk products

2.5.5. Functional foods

2.6. Methods for mapping dietary patterns

2.7. Observational and interventional studies into the effects of diet and nutrition on health

2.8. Analytical methods

2.9. Issues in analysing samples

Chapter 3: Chemometrics methods for the analysis of genomics, transcriptomics, proteomics, metabolomics, and metagenomics...

3.1. Introduction

3.2. Unsupervised and supervised pattern recognition methods

3.3. Multivariate calibration methods for developing predictive models

3.4. Statistical data integration methods

3.5. Data integration: multiblock strategies

3.6. Data integration: calibration transfer methods

3.7. Data integration: multiway/multimodal analysis methods

3.7.1. PARAFAC.

3.7.2. Tucker decomposition

3.8. Data integration: correlation-based approaches

3.9. Data integration: techniques for analysing different types of genomics datasets

3.10. Statistical data integration of different sample types

3.11. Statistical data integration of different molecular components in samples

3.12. Modelling relationships between molecular components

3.13. Conclusion and future trends

Part Two: Applications in nutrition research

Chapter 4: Application of lipidomics in nutrition research

4.1. Introduction

4.2. Lipids

4.3. Lipidomics

4.3.1. Sampling and lipid sample preparation

4.3.2. Lipid analysis

4.3.2.1. Shotgun lipidomics

4.3.2.2. LC-MS for lipid analysis

4.3.3. Data processing and bioinformatics

4.4. Lipidomics in nutrition research

4.4.1. Lipidomics in the determination of the effects of specific diets or challenge tests

4.4.2. Lipidomics in the investigation of metabolic syndrome and associated diseases

4.4.3. Lipidomics to control food quality

4.5. Conclusion and future trends

Acknowledgement

Chapter 5: Analysing human metabolic networks using metabolomics

5.1. Introduction

5.2. Metabolic network reconstruction

5.2.1. Genome-based reconstruction method

5.2.2. Biochemical reconstruction

5.2.3. Manual curation

5.3. Human metabolic networks

5.3.1. Human metabolic databases and genome-scale networks

5.3.2. Tissue-specific metabolic networks

5.3.3. Limitations

5.3.4. Exchange formats

5.4. Linking metabolomics data and metabolic network elements

5.4.1. Metabolomics dataset

5.4.2. Metabolite identifiers

5.4.3. Metabolite mapping using exact masses

5.5. Metabolism modelling, from pathways to network

5.5.1. Pathway analysis and its limitation in global approaches.

5.5.2. Overview of metabolic modelling

5.5.3. Graph-based modelling

5.6. Subnetwork extraction between identified metabolites

5.6.1. Finding reaction paths between biomarkers

5.6.2. Retrieving and improving a biological interpretation of biomarkers

5.6.3. Metabolic stories

5.6.4. Usage in metabolomics and other multi-omics analysis

5.7. Conclusion and future directions

Acknowledgements

Chapter 6: Using metabolomics to analyse the role of gut microbiota in nutrition and disease

6.1. Introduction: gut microbiota and human health

6.1.1. Gut microbiota: an extragenome organ in the human host

6.1.2. The relationships between changes in gut microbiota composition and diversity and disease

6.2. Metagenomics of gut microbiota

6.3. Metabolomics: uncovering complex host-microbe interactions

6.4. The marriage of metagenomics and metabolomics: microbiome-metabolome interactions

6.5. Future perspectives: personalised nutrition

Chapter 7: Metabotyping

7.1. Introduction

7.2. The concept of the metabotype

7.3. Examples of metabotyping with a focus on nutrition

7.4. Extension of metabotypes to include markers of dietary origin

7.5. Conclusion and future trends

7.6. Sources of further information and advice

Chapter 8: Using metabolomics to identify biomarkers for metabolic diseases

8.1. Introduction

8.2. Using metabolomics to understand the relationship between nutrition and chronic metabolic diseases

8.2.1. Acylcarnitines

8.2.2. Branched-chain amino acids and other amino acids

8.2.3. Lysophospholipids

8.2.4. Other metabolites

8.3. Cohort studies and biomarker identification

8.4. Isolating in situ biomarkers

8.5. Conclusions and future trends

References.

Chapter 9: Using metabolomics to evaluate food intake: applications in nutritional epidemiology

9.1. Introduction

9.2. Biomarkers as a complementary approach to questionnaires

9.3. Definition of the food metabolome

9.4. Metabolomics as a tool for dietary biomarker discovery

9.5. Dietary patterns and metabolomic profiles: potential use of nutritypes

9.6. Validation of putative biomarkers

9.7. The future of metabolomics in dietary assessment

9.7.1. Overcoming methodological bottlenecks in marker identification

9.7.2. Sharing of resources (databases, standard original procedures (SOPs), chemical standards, and raw data)

9.7.3. Databasing of biomarkers: development of tools and methods for routine use in large-scale cohorts

9.8. Conclusion

Chapter 10: Metabolomics and nutritional challenge tests

10.1. Introduction

10.2. Application of metabolomics to challenge tests

10.3. Conclusion and future trends

Chapter 11: Using metabolomics to describe food in detail

11.1. Introduction

11.2. Using metabolomics to assess the effects of genetic selection and modification

11.3. Using metabolomics to assess the effects of organic versus conventional farming

11.4. Using metabolomics to identify the geographical origin of food products

11.5. Using metabolomics to assess the effects of rearing conditions on the quality of meat, eggs, and fish

11.6. Using metabolomics to assess the effects of processing on food quality

11.7. Using metabolomics to assess the effects of digestion on nutrient intake from particular foods

11.8. Conclusion

Appendix: abbreviations

Chapter 12: Future perspectives for metabolomics in nutrition research

12.1. Introduction

12.2. Metabolites identification and biological relevance

12.3. In vivo metabolomics.

12.4. Conclusion

Index.

Notes:

Bibliographic Level Mode of Issuance: Monograph

Includes bibliographical references at the end of each chapters and index.

Description based on online resource; title from PDF title page (ebrary, viewed January 7, 2015).

ISBN:

1-78242-092-4

1-78242-084-3

OCLC:

898421810