Nutrition proteomics and biomarker discovery

Nutrigenomics: lessons learned and future perspectives

The omics technologies of metabolomics, transcriptomics, proteomics, and metagenomics are playing an increasingly important role in nutrition science. With the emergence of the concept of precision nutrition and the need to understand individual responses to dietary interventions, it is an opportune time to examine the impact of these tools to date in human nutrition studies. Advances in our mechanistic understanding of dietary interventions were realized through incorporation of metabolomics, proteomics, and, more recently, metagenomics. A common observation across the studies was the low intra-individual variability of the omics measurements and the high inter-individual variation. Harnessing this data for use in the development of precision nutrition will be important. Metabolomics in particular has played a key role in the development of biomarkers of food intake in an effort to enhance the accuracy of dietary assessments. Further work is needed to realize the full potential of such biomarkers and to demonstrate integration with current strategies, with the goal of overcoming the well-established limitations of self-reported approaches. Although many of the nutrigenomic studies performed to date were labelled as proof-of-concept or pilot studies, there is ample evidence to support the use of these technologies in nutrition science. Incorporating omic technologies from the start of study designs will ensure that studies are sufficiently powered for such data. Furthermore, multi-disciplinary collaborations are likely to become even more important to aid analyses and interpretation of the data.

Nutrigenomics, the Microbiome, and Gene-Environment Interactions: New Directions in Cardiovascular Disease Research, Prevention, and Treatment: A Scientific Statement From the American Heart Association

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention.

Beneficial effects of omega-3 fatty acids in the proteome of high-density lipoprotein proteome

Background

Omega-3 poly-unsaturated fatty acids (ω-3 PUFAs) have demonstrated to be beneficial in the prevention of cardiovascular disease, however, the mechanisms by which they perform their cardiovascular protection have not been clarified. Intriguingly, some of these protective effects have also been linked to HDL. The hypothesis of this study was that ω-3 PUFAs could modify the protein cargo of HDL particle in a triglyceride non-dependent mode. The objective of the study was to compare the proteome of HDL before and after ω-3 PUFAs supplemented diet.

Methods

A comparative proteomic analysis in 6 smoker subjects HDL before and after a 5 weeks ω-3 PUFAs enriched diet has been performed.

Results

Among the altered proteins, clusterin, paraoxonase, and apoAI were found to increase, while fibronectin, α-1-antitrypsin, complement C1r subcomponent and complement factor H decreased after diet supplementation with ω-3 PUFAs. Immunodetection assays confirmed these results. The up-regulated proteins are related to anti-oxidant, anti-inflammatory and anti-atherosclerotic properties of HDL, while the down-regulated proteins are related to regulation of complement activation and acute phase response.

Conclusions

Despite the low number of subjects included in the study, our findings demonstrate that ω-3 PUFAs supplementation modifies lipoprotein containing apoAI (LpAI) proteome and suggest that these protein changes improve the functionality of the particle.

Proteomic approaches to predict bioavailability of fatty acids and their influence on cancer and chronic disease prevention

A low intake of fish and PUFA and high dietary trans- and SFA are considered to be among the main preventable causes of death. Unfortunately, epidemiological and preclinical studies have yet to identify biomarkers that accurately predict the influence of fatty acid intake on risk of chronic diseases, including cancer. Changes in protein profile and post-translational modifications in tissue and biofluids may offer important clues about the impact of fatty acids on the etiology of chronic diseases. However, conventional protein methodologies are not adequate for assessing the impact of fatty acids on protein expression patterns and modifications and the discovery of protein biomarkers that predict changes in disease risk and progression in response to fatty acid intake. Although fluctuations in protein structure and abundance and inter-individual variability often mask subtle effects caused by dietary intervention, modern proteomic platforms offer tremendous opportunities to increase the sensitivity of protein analysis in tissues and biofluids (plasma, urine) and elucidate the effects of fatty acids on regulation of protein networks. Unfortunately, the number of studies that adopted proteomic tools to investigate the impact of fatty acids on disease risk and progression is quite small. The future success of proteomics in the discovery of biomarkers of fatty acid nutrition requires improved accessibility and standardization of proteomic methodologies, validation of quantitative and qualitative protein changes (e.g., expression levels, post-translational modifications) induced by fatty acids, and application of bioinformatic tools that can inform about the cause-effect relationships between fatty acid intake and health response.

Nutriproteomics: technologies and applications for identification and quantification of biomarkers and ingredients

Nutrition refers to the process by which a living organism ingests and digests food and uses the nutrients therein for growth, tissue maintenance and all other functions essential to life. Food components interact with our body at molecular, cellular, organ and system level. Nutrients come in complex mixtures, in which the presence and concentration of single compounds as well as their interactions with other compounds and the food matrix influence their bioavailability and bioefficacy. Traditionally, nutrition research mainly concentrated on supplying nutrients of quality to nourish populations and on preventing specific nutrient deficiencies. More recently, it investigates health-related aspects of individual ingredients or of complete diets, in view of health promotion, performance optimisation, disease prevention and risk assessment. This review focuses on proteins and peptides, their role as nutrients and biomarkers and on the technologies developed for their analysis. In the first part of this review, we provide insights into the way proteins are currently characterised and analysed using classical and emerging proteomic approaches. The scope of the second part is to review major applications of proteomics to nutrition, from characterisation of food proteins and peptides, via investigation of health-related food benefits to understanding disease-related mechanisms.

2D-electrophoresis and multiplex immunoassay proteomic analysis of different body fluids and cellular components reveal known and novel markers for extended fasting

Background

Proteomic technologies applied for profiling human biofluids and blood cells are considered to reveal new biomarkers of exposure or provide insights into novel mechanisms of adaptation.

Methods

Both a non-targeted (classical 2D-electrophoresis combined with mass spectrometry) as well as a targeted proteomic approach (multiplex immunoassay) were applied to investigate how fasting for 36 h, as compared to 12 h, affects the proteome of platelets, peripheral blood mononuclear cells (PBMC), plasma, urine and saliva collected from ten healthy volunteers.

Results

Between-subject variability was highest in the plasma proteome and lowest in the PBMC proteome. Random Forests analysis performed on the entire dataset revealed that changes in the level of the RhoGDI2 protein in PBMC and plasma ApoA4 levels were the two most obvious biomarkers of an extended fasting. Random Forests (RF) analysis of the multiplex immunoassay data revealed leptin and MMP-3 as biomarkers for extended fasting. However, high between-subject variability may have masked the extended fasting effects in the proteome of the biofluids and blood cells.

Conclusions

Identification of significantly changed proteins in biofluids and blood cells using a non-targeted approach, together with the outcome of targeted analysis revealed both known and novel markers for a 36 h fasting period, including the cellular proteins RhoGDI2 and CLIC1, and plasma proteins ApoA4, leptin and MMP-3. The PBMC proteome exhibited the lowest between-subject variability and therefore these cells appear to represent the best biosamples for biomarker discovery in human nutrigenomics.