Performing Department
(N/A)
Non Technical Summary
The field of food science is growing rapidly to develop new substances with added nutritional values and discover new therapeutic benefits such as a source of natural antioxidants, health-promoting materials, nutraceuticals, and potential functional foods. Identifying and quantifying nutritional benefits in food ingredients and evaluating their biological activities are essential to gauge their efficacy and safe applications. The traditional method of nutritional profiles using mass-spectrometry measurements provides knowledge of the active molecules. Still, it cannot provide any information on their biological activities that require in vivo models. Efficacy studies with higher mammals are costly, highly regulated, and take several years to complete. To overcome these challenges, we propose to develop a C. elegans-based alternative to animal testing strategy to assess the health benefits of ingredients available in food, herbal preparations, plants, and derived products. C. elegans can provide ethical testing while preserving many signaling pathways governed by orthologous genes and CRISPR-assisted gene editing that aid in capturing toxicity and health benefits in amulti-organ intact organism. Despite these advantages, current-day C. elegans-based assays suffer from low-throughput or low-resolution imaging technologies.Our high-resolution imaging platform with an automated image analysis pipeline will facilitate rapid detection of multiple phenotypes related to lipid storage, stress level, gut health, growth, and reproductive health. We will test the robustness of our assay and validate using six food ingredients in consultation with our industry and academia collaborators. In addition, our assay will also help identify adverse effects, allowing our customers to define safe dose limits for their ingredients. Our technology can help determine the health benefits of novel food products and new materials, helping USDA Food Science and Nutrition to meet the long-term goals of producing novel food products that can improve health and avoid adverse effects on human health outcomes.
Animal Health Component
0%
Research Effort Categories
Basic
50%
Applied
(N/A)
Developmental
50%
Goals / Objectives
Goal 1: Develop a battery of assays to assess the health benefits of food ingredients.Develop assays for quantifying lipid storage, gut health, and oxidative stress responses in C. elegans.Develop an automated image analysis of these assays for high-throughput quantification.Test the health benefits of 6 food ingredients using these assays.Goal 2: Perform the toxicology assessment of 6 food ingredients.Study multiple toxicology using phenotypes in C. elegans.Restudy in a C. elegans strain with increased cuticle permeability.Expected outcomes: Develop 3 novel assays to quantify health-benefits-related outcomes and show the reproducibility of data from negative control populations (0.2% DMSO) over 3 independent experiments with <30% CV. Quantify the effects of 6 ingredientsand identify the EC50 with 95% confidence. Find LOAELs for all ingredients with effects in the dose range testable in wild-type and cuticle mutants. Show >5-fold increased sensitivity of cuticle mutants to certain ingredients.
Project Methods
We propose to develop complementary assays using C. elegans models to allow high throughput analysis of the effects of ingredients and their combinations. We will analyze C. elegans'gut, fat content,andoxidative stress levels.These endpoints will be used for judging the nutritional value of food. Certain food ingredients affect gut permeability,lipid metabolism, andoxidative stress. We will develop and optimize the assays to capture these phenotypes using our microfluidics-based phenotypic imaging system. Gut permeability will be assessed by feeding worms with a non-toxic fluorescent dye to which the gut is normally impermeable. We will develop automated image analysis algorithms to measure the extent of the dye outside of the intestinal boundary to quantify the increase in gut permeability. Lipid storage will be measured by feeding the worms with Nile Red, a dye that is soluble and fluorescent in lipids, and measuring the fluorescence signal. Oxidative stress will be calculated using a fluorescent reporter strain gst-4::GFP,upregulated bygst-4 and showing an increase in the GFP signal. Once we establish the assay with known controls and automate the image processing pipeline, we will test 6 food ingredients with our assay.The health benefit parameters will be accompanied by toxicology-related parameters. We will analyzethe developmental parameters (body length, area, and volume) and reproduction health (in-utero embryo counts in differentdevelopmental stages). The parameters will be used to estimate a safe dose in worms from the Hill-function fit of the multiple dose curves and calculate thelowest observed adverse effect level (LOAEL) values. We will test the ingredients in a cuticle mutant to characterize how the toxicity endpoint changes upon an increase in the intake and bioavailability of the ingredients.The performance of the assay will be quantified using batch-to-batch variability. We will evaluate the coefficient of variance (CVfrom 3 replicates) to keep the valuebelow 30%. We will calculate theeffective concentration values (EC50) for each of the ingredients with high statistical power. We will also find theLOAELs for each ingredient in ourassay.