Nutritional Proteomics: Methods and Concepts for Research in Nutritional Science

Identification of Protein Biomarkers of the Dietary Approaches to Stop Hypertension Diet in Randomized Feeding Studies and Validation in an Observational Study

Background The Dietary Approaches to Stop Hypertension (DASH) diet is recommended for cardiovascular disease prevention. We aimed to identify protein biomarkers of the DASH diet using data from 2 randomized feeding studies and validate them in an observational study, the ARIC (Atherosclerosis Risk in Communities) study. Methods and Results Large-scale proteomic profiling was conducted in serum specimens (SomaLogic) collected at the end of 8-week and 4-week DASH diet interventions in multicenter, randomized controlled feeding studies of the DASH trial (N=215) and the DASH-Sodium trial (N=396), respectively. Multivariable linear regression models were used to compare the relative abundance of 7241 proteins between the DASH and control diet interventions. Estimates from the 2 trials were meta-analyzed using fixed-effects models. We validated significant proteins in the ARIC study (N=10 490) using the DASH diet score. At a false discovery rate <0.05, there were 71 proteins that were different between the DASH diet and control diet in the DASH and DASH-Sodium trials. Nineteen proteins were validated in the ARIC study. The 19 proteins collectively improved the prediction of the DASH diet intervention in the feeding studies (range of difference in C statistics, 0.267-0.313; P<0.001 for both tests) and the DASH diet score in the ARIC study (difference in C statistics, 0.017; P<0.001) beyond participant characteristics. Conclusions We identified 19 proteins robustly associated with the DASH diet in 3 studies, which may serve as biomarkers of the DASH diet. These results suggest potential pathways that are impacted by consumption of the DASH diet. Registration URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03403166, NCT00000608.

Nutrition and Rheumatoid Arthritis in the 'Omics' Era

Modern high-throughput 'omics' science tools (including genomics, transcriptomics, proteomics, metabolomics and microbiomics) are currently being applied to nutritional sciences to unravel the fundamental processes of health effects ascribed to particular nutrients in humans and to contribute to more precise nutritional advice. Diet and food components are key environmental factors that interact with the genome, transcriptome, proteome, metabolome and the microbiota, and this life-long interplay defines health and diseases state of the individual. Rheumatoid arthritis (RA) is a chronic autoimmune disease featured by a systemic immune-inflammatory response, in genetically susceptible individuals exposed to environmental triggers, including diet. In recent years increasing evidences suggested that nutritional factors and gut microbiome have a central role in RA risk and progression. The aim of this review is to summarize the main and most recent applications of 'omics' technologies in human nutrition and in RA research, examining the possible influences of some nutrients and nutritional patterns on RA pathogenesis, following a nutrigenomics approach. The opportunities and challenges of novel 'omics technologies' in the exploration of new avenues in RA and nutritional research to prevent and manage RA will be also discussed.

Proteomics Analysis Reveals the Implications of Cytoskeleton and Mitochondria in the Response of the Rat Brain to Starvation

Long-term starvation provokes a metabolic response in the brain to adapt to the lack of nutrient intake and to maintain the physiology of this organ. Here, we study the changes in the global proteomic profile of the rat brain after a seven-day period of food deprivation, to further our understanding of the biochemical and cellular mechanisms underlying the situations without food. We have used two-dimensional electrophoresis followed by mass spectrometry (2D-MS) in order to identify proteins differentially expressed during prolonged food deprivation. After the comparison of the protein profiles, 22 brain proteins were found with altered expression. Analysis by peptide mass fingerprinting and MS/MS (matrix-assisted laser desorption-ionization-time of flight mass spectrometer, MALDI-TOF/TOF) enabled the identification of 14 proteins differentially expressed that were divided into 3 categories: (1) energy catabolism and mitochondrial proteins; (2) chaperone proteins; and (3) cytoskeleton, exocytosis, and calcium. Changes in the expression of six proteins, identified by the 2D-MS proteomics procedure, were corroborated by a nanoliquid chromatography-mass spectrometry proteomics procedure (nLC-MS). Our results show that long-term starvation compromises essential functions of the brain related with energetic metabolism, synapsis, and the transmission of nervous impulse.

Employing proteomics to understand the effects of nutritional intervention in cancer treatment

Lifestyle optimizations are implementable changes that can have an impact on health and disease. Nutrition is a lifestyle optimization that has been shown to be of great importance in cancer initiation, progression, and metastasis. Dozens of clinical trials are currently in progress that focus on the nutritional modifications that cancer patients can make prior to and during medical care that increase the efficacy of treatment. In this review, we discuss various nutritional inventions for cancer patients and the analytical approaches to characterize the downstream molecular effects. We first begin by briefly explaining the many different forms of nutritional intervention currently being used in cancer treatment as well as their motivating biology. The forms of nutrient modulation described in this review include calorie restriction, the different practices of fasting, and carbohydrate restriction. The review then shifts to explain how proteomics is used to determine biomarkers of cancer and how it can be utilized in the future to determine the metabolic phenotype of a tumor, and inform physicians if nutritional intervention should be recommended for a cancer patient. Nutrigenomics aims to understand the relationship of nutrients and gene expression and can be used to understand the downstream molecular effects of nutrition restriction, partially through proteomic analysis. Proteomics is just beginning to be used as cancer diagnostic and predictive tools. However, these approaches have not been used to their full potential to understand nutritional intervention in cancer. Graphical abstract ᅟ.

The Use of "Omics" in Lactation Research in Dairy Cows

“Omics” is the application of genomics, transcriptomics, proteomics, and metabolomics in biological research. Over the years, tremendous amounts of biological information has been gathered regarding the changes in gene, mRNA and protein expressions as well as metabolites in different physiological conditions and regulations, which has greatly advanced our understanding of the regulation of many physiological and pathophysiological processes. The aim of this review is to comprehensively describe the advances in our knowledge regarding lactation mainly in dairy cows that were obtained from the “omics” studies. The “omics” technologies have continuously been preferred as the technical tools in lactation research aiming to develop new nutritional, genetic, and management strategies to improve milk production and milk quality in dairy cows.

The impact of micronutrient status on health: correlation network analysis to understand the role of micronutrients in metabolic-inflammatory processes regulating homeostasis and phenotypic flexibility

Background

Vitamins and carotenoids are key micronutrients facilitating the maintenance of health, as evidenced by the increased risk of disease with low intake. Optimal phenotypic flexibility, i.e., the ability to respond to a physiological challenge, is an essential indicator of health status. Therefore, health can be measured by applying a challenge test and monitoring the response of relevant phenotypic processes. In this study, we assessed the correlation of three fat-soluble vitamins, (i.e., vitamin A or retinol, vitamin D₃, two homologues of vitamin E) and four carotenoids (i.e., α-carotene, β-carotene, β-cryptoxanthin, and lycopene), with characteristics of metabolic and inflammatory parameters at baseline and in response to a nutritional challenge test (NCT) in a group of 36 overweight and obese male subjects, using proteomics and metabolomics platforms. The phenotypic flexibility concept implies that health can be measured by the ability to adapt to a NCT, which may offer a more sensitive way to assess changes in health status of healthy subjects.

Results

Correlation analyses of results after overnight fasting revealed a rather evenly distributed network in a number of relatively strong correlations per micronutrient, with minor overlap between correlation profiles of each compound. Correlation analyses of challenge response profiles for metabolite and protein parameters with micronutrient status revealed a network that is more skewed towards α-carotene and γ-tocopherol suggesting a more prominent role for these micronutrients in the maintenance of phenotypic flexibility. Comparison of the networks revealed that there is merely overlap of two parameters (inositol and oleic acid (C18:1)) affirming that there is a specific biomarker response profile upon NCT.

Conclusions

Our study shows that applying the challenge test concept is able to reveal previously unidentified correlations between specific micronutrients and health-related processes, with potential relevance for maintenance of health that were not observed by correlating homeostatic measurements. This approach will contribute to insights on the influence of micronutrients on health and help to create efficient micronutrient intervention programs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12263-017-0553-7) contains supplementary material, which is available to authorized users.

Novel regulatory roles of omega-3 fatty acids in metabolic pathways: a proteomics approach

Background

Omega-3 polyunsaturated fatty acids (n-3 PUFA) have been shown to alleviate the symptoms of metabolic disorders, such as heart disease, diabetes, obesity and insulin resistance. Several putative mechanisms by which n-3 PUFA elicit beneficial health effects have been proposed; however, there is still a shortage of knowledge on the proteins and pathways that are regulated by n-3 PUFA.

Methods

Using two dimensional polyacrylamide gel electrophoresis (2D-PAGE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, we investigated the effects of diets high or low in n-3 PUFA on hepatic proteomic profile of C57BL/6 mice.

Results

The findings show for the first time that high dietary n-3 PUFA reduced the expression of regucalcin, adenosine kinase and aldehyde dehydrogenase. On the other hand, diets high in n-3 PUFA increased the expression of apolipoprotein A-I, S-adenosylmethionine synthase, fructose-1, 6-bisphosphatase, ketohexokinase, malate dehydrogenase, GTP-specific succinyl CoA synthase, ornithine aminotransferase and protein disulfide isomerase-A3.

Conclusions

Our findings revealed for the first time that n-3 PUFA causes alterations in several novel functional proteins involved in regulating lipid, carbohydrate, one-carbon, citric acid cycle and protein metabolism, suggesting integrated regulation of metabolic pathways. These novel proteins are potential targets to develop therapeutic strategies against metabolic disorders.

The plasma proteome identifies expected and novel proteins correlated with micronutrient status in undernourished Nepalese children

Micronutrient deficiencies are common in undernourished societies yet remain inadequately assessed due to the complexity and costs of existing assays. A plasma proteomics-based approach holds promise in quantifying multiple nutrient:protein associations that reflect biological function and nutritional status. To validate this concept, in plasma samples of a cohort of 500 6- to 8-y-old Nepalese children, we estimated cross-sectional correlations between vitamins A (retinol), D (25-hydroxyvitamin D), and E (α-tocopherol), copper, and selenium, measured by conventional assays, and relative abundance of their major plasma-bound proteins, measured by quantitative proteomics using 8-plex iTRAQ mass tags. The prevalence of low-to-deficient status was 8.8% (<0.70 μmol/L) for retinol, 19.2% (<50 nmol/L) for 25-hydroxyvitamin D, 17.6% (<9.3 μmol/L) for α-tocopherol, 0% (<10 μmol/L) for copper, and 13.6% (<0.6 μmol/L) for selenium. We identified 4705 proteins, 982 in >50 children. Employing a linear mixed effects model, we observed the following correlations: retinol:retinol-binding protein 4 (r = 0.88), 25-hydroxyvitamin D:vitamin D-binding protein (r = 0.58), α-tocopherol:apolipoprotein C-III (r = 0.64), copper:ceruloplasmin (r = 0.65), and selenium:selenoprotein P isoform 1 (r = 0.79) (all P < 0.0001), passing a false discovery rate threshold of 1% (based on P value-derived q values). Individual proteins explained 34-77% (R(2)) of variation in their respective nutrient concentration. Adding second proteins to models raised R(2) to 48-79%, demonstrating a potential to explain additional variation in nutrient concentration by this strategy. Plasma proteomics can identify and quantify protein biomarkers of micronutrient status in undernourished children. The maternal micronutrient supplementation trial, from which data were derived as a follow-up activity, was registered at clinicaltrials.gov as NCT00115271.

Proteomic profiling of the rat hypothalamus

Background

The hypothalamus plays a pivotal role in numerous mechanisms highly relevant to the maintenance of body homeostasis, such as the control of food intake and energy expenditure. Impairment of these mechanisms has been associated with the metabolic disturbances involved in the pathogenesis of obesity. Since rodent species constitute important models for metabolism studies and the rat hypothalamus is poorly characterized by proteomic strategies, we performed experiments aimed at constructing a two-dimensional gel electrophoresis (2-DE) profile of rat hypothalamus proteins.

Results

As a first step, we established the best conditions for tissue collection and protein extraction, quantification and separation. The extraction buffer composition selected for proteome characterization of rat hypothalamus was urea 7 M, thiourea 2 M, CHAPS 4%, Triton X-100 0.5%, followed by a precipitation step with chloroform/methanol. Two-dimensional (2-D) gels of hypothalamic extracts from four-month-old rats were analyzed; the protein spots were digested and identified by using tandem mass spectrometry and database query using the protein search engine MASCOT. Eighty-six hypothalamic proteins were identified, the majority of which were classified as participating in metabolic processes, consistent with the finding of a large number of proteins with catalytic activity. Genes encoding proteins identified in this study have been related to obesity development.

Conclusion

The present results indicate that the 2-DE technique will be useful for nutritional studies focusing on hypothalamic proteins. The data presented herein will serve as a reference database for studies testing the effects of dietary manipulations on hypothalamic proteome. We trust that these experiments will lead to important knowledge on protein targets of nutritional variables potentially able to affect the complex central nervous system control of energy homeostasis.

Antioxidative activity of propolis extract in yeast cells

The antioxidative activities of propolis and its main phenolic compounds, caffeic acid, p-coumaric acid, ferulic acid, and caffeic acid phenethyl ester, were investigated in the yeast Saccharomyces cerevisiae. After 1 h of exposure of the yeast cells, their intracellular oxidation was measured using 2',7'-dichlorofluorescein. Yeast cells exposed to 96% ethanolic extracts of propolis in DMSO (EEP) showed decreased intracellular oxidation, with no significant differences seen for the individual phenolic compounds. However, cellular uptake was seen only for a moderately polar fraction of EEP (E2) and caffeic acid phenethyl ester. The EEP antioxidative activity thus resulted from this E2 fraction of EEP. The influence of EEP was also investigated at the mitochondrial proteome level, by analyzing its profile after 1 h of exposure of the yeast cells to EEP and E2. Changes in the levels of antioxidative proteins and proteins involved in ATP synthesis were seen.

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.

Metabolomic characterization of Italian sweet pepper (Capsicum annum L.) by means of HRMAS-NMR spectroscopy and multivariate analysis

HRMAS-NMR spectroscopy was used to assess the metabolic profile of sweet pepper (Capsicum Annum L.). One-dimensional and two-dimensional NMR spectra, performed directly on sample pieces of few milligrams, hence without any chemical and/or physical manipulation, allowed the assignment of several compounds. Organic acids, fatty acids, amino acids, and minor compounds such as trigonelline, C4-substituted pyridine, choline, and cinnamic derivatives were observed with a single experiment. A significant discrimination between the two sweet pepper varieties was found by using partial least-squares projections to latent structures discrimination analysis (PLS-DA). The metabolites contributing predominantly to such differentiation were sugars and organic and fatty acids. Also a partial separation according to the geographical origin was obtained always by analyzing the NMR data with PLS-DA. Some of the discriminating molecules are peculiar for pepper and contribute to define the overall commercial and organoleptic quality so that HRMAS-NMR proved to be a complementary analysis to standard tools used in food science and, in principle, can be applied to any foodstuff.

Cancer predisposition in diabetics: risk factors considered for predictive diagnostics and targeted preventive measures

Diabetes mellitus (DM) is a lifelong progressive disease with high morbidity and mortality worldwide. Whereas cardiovascular complications are well-known for DM, increasing evidence indicates that diabetics are predisposed to cancer. Understanding of molecular pathomechanisms of cancer in DM is of great importance. Dysregulation of glucose/insulin homeostasis leads to increased production of Reactive Oxygen/Nitrogen Species (ROS/RNS) and consequent damage to chromosomal/mitochondrial DNA, a frequent finding in DM. Long-term accumulation of modified/damaged DNA is well-acknowledged as triggering cancer. DNA-repair is a highly energy consuming process provoking increased mitochondrial activity. Particularly dangerous is a provoked activity of damaged mitochondria leading to a “vicious circle” lowering energy supply and potentiating ROS/RNS production. Mitochondrial dysfunction may be implicated in pathomechanisms of diabetes-related cancer. High risk for infectious disorders and induced viral proto-oncogenic activity may further contribute to cancer provocation. Much attention should be focused on preventive measures in diabetic healthcare, in order to restrict severe diabetes-related complications.

Advances in Nutrigenomics research: novel and future analytical approaches to investigate the biological activity of natural compounds and food functions

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend, Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that aims to elucidate how diet can influence human health. It is already well known that bioactive food compounds can interact with genes affecting transcription factors, protein expression and metabolite production. The study of these complex interactions requires the development of advanced analytical approaches combined with bioinformatics. Thus, to carry out these studies Transcriptomics, Proteomics and Metabolomics approaches are employed together with an adequate integration of the information that they provide. In this article, an overview of the current methodologies and a thorough revision of the advances in analytical technologies and their possibilities for future developments and applications in the field of Nutrigenomics is provided.

Studying the central control of food intake and obesity in rats

The central nervous system regulates energy intake and expenditure through a complex network of neurotransmitters and neuromodulators. It is of great interest to understand the relevance of these systems to the physiological control of energy balance and to the disturbances of obesity. The present paper discusses some of the methods to address this field used at the laboratory of Endocrine Physiology of Universidade Federal de São Paulo. Initially, different experimental models of rat obesity are presented, namely the hypothalamic induced monosodium glutamate model, the Zucker genetic model, and the dietary model. The principles of brain microdialysis are also presented, the technique applied to obtain representative samples of the extracellular fluid of brain sites involved in feeding control. The microdialysate levels of serotonin, an important anorexigenic neurotransmitter, are determined by HPLC with electrochemical detection. The immunoblot technique (Western blot) is used to determine hypothalamic levels of proteins relevant to the anorexigenic effect of serotonin and to analyze the acute activation of the insulin signaling cascade in the hypothalamus. The final section addresses the potential applications of proteomics in the study of the central control of feeding.

Quantitative mass spectrometry as a tool for nutritional proteomics

The goal of nutritional science is to determine the effect of dietary components. Proteomics has emerged as a method to study proteins on a large scale. The proteomic information gathered from a sample, whether a biological fluid, cell, or tissue, includes not only the identities of proteins present but also their quantities and posttranslational modifications. Recent advances in mass spectrometry make it possible to accurately measure concentrations of thousands of proteins derived from such complex biological samples. Quantitative data will provide increased understanding of the dynamic changes in the proteome induced by dietary components.

Proteomic methodological recommendations for studies involving human plasma, platelets, and peripheral blood mononuclear cells

This study was designed to develop, optimize and validate protocols for blood processing prior to proteomic analysis of plasma, platelets and peripheral blood mononuclear cells (PBMC) and to determine analytical variation of a single sample of depleted plasma, platelet and PBMC proteins within and between four laboratories each using their own standard operating protocols for 2D gel electrophoresis. Plasma depleted either using the Beckman Coulter IgY-12 proteome partitioning kit or the Amersham albumin and IgG depletion columns gave good quality gels, but reproducibility appeared better with the single-use immuno-affinity column. The use of the Millipore Filter Device for protein concentration gave a 16% ( p < 0.005) higher recovery of protein in flow-through sample compared with acetone precipitation. The use of OptiPrep gave the lowest level of platelet contamination (1:0.8) during the isolation of PBMC from blood. Several proteins (among which are alpha-tropomyosin, fibrinogen and coagulation factor XIII A) were identified that may be used as biomarkers of platelet contamination in future studies. When identifying preselected spots, at least three out of the four centers found similar identities for 10 out of the 10 plasma proteins, 8 out of the 10 platelet proteins and 8 out of the 10 PBMC proteins. The discrepancy in spot identifications has been described before and may be explained by the mis-selection of spots due to laboratory-to-laboratory variation in gel formats, low scores on the peptide analysis leading to no or only tentative identifications, or incomplete resolution of different proteins in what appears as a single abundant spot. The average within-laboratory coefficient of variation (CV) for each of the matched spots after automatic matching using either PDQuest or ProteomWeaver software ranged between 18 and 69% for depleted plasma proteins, between 21 and 55% for platelet proteins, and between 22 and 38% for PBMC proteins. Subsequent manual matching improved the CV with on average between 1 and 16%. The average between laboratory CV for each of the matched spots after automatic matching ranged between 4 and 54% for depleted plasma proteins, between 5 and 60% for platelet proteins, and between 18 and 70% for PBMC proteins. This variation must be considered when designing sufficiently powered studies that use proteomics tools for biomarker discovery. The use of tricine in the running buffer for the second dimension appears to enhance the resolution of proteins especially in the high molecular weight range.

High throughput ‘omics’ approaches to assess the effects of phytochemicals in human health studies

Human health is affected by many factors. Diet and inherited genes play an important role. Food constituents, including secondary metabolites of fruits and vegetables, may interact directly with DNA via methylation and changes in expression profiles (mRNA, proteins) which results in metabolite content changes. Many studies have shown that food constituents may affect human health and the exact knowledge of genotypes and food constituent interactions with both genes and proteins may delay or prevent the onset of diseases. Many high throughput methods have been employed to get some insight into the whole process and several examples of successful research, namely in the field of genomics and transcriptomics, exist. Studies on epigenetics and RNome significance have been launched. Proteomics and metabolomics need to encompass large numbers of experiments and linked data. Due to the nature of the proteins, as well as due to the properties of various metabolites, experimental approaches require the use of comprehensive high throughput methods and a sufficiency of analysed tissue or body fluids. In this contribution, we describe the basic tools currently used in nutrigenomics studies and indicate the general requirements for future technology methodological routings.

The plasma proteome, adductome and idiosyncratic toxicity in toxicoproteomics research

Toxicoproteomics uses the discovery potential of proteomics in toxicology research by applying global protein measurement technologies to biofluids and tissues after host exposure to injurious agents. Toxicoproteomic studies thus far have focused on protein profiling of major organs and biofluids such as liver and blood in preclinical species exposed to model toxicants. The slow pace of discovery for new biomarkers, toxicity signatures and mechanistic insights is partially due to the limited proteome coverage derived from analysis of native organs, tissues and body fluids by traditional proteomic platforms. Improved toxicoproteomic analysis would result by combining higher data density LC-MS/MS platforms with stable isotope labelled peptides and parallel use of complementary platforms. Study designs that remove abundant proteins from biofluids, enrich subcellular structures and include cell specific isolation from heterogeneous tissues would greatly increase differential expression capabilities. By leveraging resources from immunology, cell biology and nutrition research communities, toxicoproteomics could make particular contributions in three inter-related areas to advance mechanistic insights and biomarker development: the plasma proteome and circulating microparticles, the adductome and idiosyncratic toxicity.