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

Bioactive components in Bambara groundnut (Vigna subterraenea (L.) Verdc) as a potential source of nutraceutical ingredients

The utilization of nutraceuticals on a global scale has significantly increased over the past few years due to their reported health benefits and consumer's reluctance to consume synthetic drugs. This paper provides information regarding new and potential value added uses of biologically active compounds in Bambara groundnut (BGN) as ingredients that could be further researched and exploited for various applications. Nutraceutical is a food or part of food that apart from providing basic nutrients, offers medicinal benefits either by prevention and or treatment of an illness. BGN is a legume with rich nutrient profile that is under exploited industrially. It is widely used in African traditional medicine for its various health outcome, but has not been explored scientifically for its numerous nutraceutical potentials. Compared to beans BGN has greater quantity of soluble fiber and also have high dietary fiber. It is rich in polyphenolic compound which include flavonoids subgroups like flavonols, flavanols, anthocyanindins, isoflavones and phenolic acids: both benzoic acid and cinnamic acid derivatives, biologically active polyunsaturated fatty acids, proteins and peptides, antioxidant vitamins and minerals. The rising interest and emphasis in plant-based biologically active components (nutraceuticals) for various health promotion, has positioned this African legume as a potential source of nutraceutical ingredients (bioactive components) that could be exploited for improved nutrition and health.

Biomarkers of Nutrition and Health: New Tools for New Approaches

A main challenge in nutritional studies is the valid and reliable assessment of food intake, as well as its effects on the body. Generally, food intake measurement is based on self-reported dietary intake questionnaires, which have inherent limitations. They can be overcome by the use of biomarkers, capable of objectively assessing food consumption without the bias of self-reported dietary assessment. Another major goal is to determine the biological effects of foods and their impact on health. Systems analysis of dynamic responses may help to identify biomarkers indicative of intake and effects on the body at the same time, possibly in relation to individuals' health/disease states. Such biomarkers could be used to quantify intake and validate intake questionnaires, analyse physiological or pathological responses to certain food components or diets, identify persons with specific dietary deficiency, provide information on inter-individual variations or help to formulate personalized dietary recommendations to achieve optimal health for particular phenotypes, currently referred as "precision nutrition." In this regard, holistic approaches using global analysis methods (omics approaches), capable of gathering high amounts of data, appear to be very useful to identify new biomarkers and to enhance our understanding of the role of food in health and disease.

The Role of Clinical Proteomics, Lipidomics, and Genomics in the Diagnosis of Alzheimer's Disease

The early diagnosis of Alzheimer’s disease (AD) has become important to the reversal and treatment of neurodegeneration, which may be relevant to premature brain aging that is associated with chronic disease progression. Clinical proteomics allows the detection of various proteins in fluids such as the urine, plasma, and cerebrospinal fluid for the diagnosis of AD. Interest in lipidomics has accelerated with plasma testing for various lipid biomarkers that may with clinical proteomics provide a more reproducible diagnosis for early brain aging that is connected to other chronic diseases. The combination of proteomics with lipidomics may decrease the biological variability between studies and provide reproducible results that detect a community’s susceptibility to AD. The diagnosis of chronic disease associated with AD that now involves genomics may provide increased sensitivity to avoid inadvertent errors related to plasma versus cerebrospinal fluid testing by proteomics and lipidomics that identify new disease biomarkers in body fluids, cells, and tissues. The diagnosis of AD by various plasma biomarkers with clinical proteomics may now require the involvement of lipidomics and genomics to provide interpretation of proteomic results from various laboratories around the world.

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.

The NutriChip project – translating technology into nutritional knowledge

Advances in food transformation have dramatically increased the diversity of products on the market and, consequently, exposed consumers to a complex spectrum of bioactive nutrients whose potential risks and benefits have mostly not been confidently demonstrated. Therefore, tools are needed to efficiently screen products for selected physiological properties before they enter the market. NutriChip is an interdisciplinary modular project funded by the Swiss programme Nano-Tera, which groups scientists from several areas of research with the aim of developing analytical strategies that will enable functional screening of foods. The project focuses on postprandial inflammatory stress, which potentially contributes to the development of chronic inflammatory diseases. The first module of the NutriChip project is composed of three in vitro biochemical steps that mimic the digestion process, intestinal absorption, and subsequent modulation of immune cells by the bioavailable nutrients. The second module is a miniaturised form of the first module (gut-on-a-chip) that integrates a microfluidic-based cell co-culture system and super-resolution imaging technologies to provide a physiologically relevant fluid flow environment and allows sensitive real-time analysis of the products screened in vitro. The third module aims at validating the in vitro screening model by assessing the nutritional properties of selected food products in humans. Because of the immunomodulatory properties of milk as well as its amenability to technological transformation, dairy products have been selected as model foods. The NutriChip project reflects the opening of food and nutrition sciences to state-of-the-art technologies, a key step in the translation of transdisciplinary knowledge into nutritional advice.