Performing Department
(N/A)
Non Technical Summary
Some foods, such as cereals, nuts, fruits, and coffee beans, are susceptible to certain molds or fungi that produce toxins known as mycotoxins. Consumption of mycotoxins-contaminated food can result in various toxicological effects such as toxic hepatitis, edema, hemorrhage, and kidney failure. The US Food and Drug Administration and World Health Organization have released strict regulatory guidelines for the major mycotoxin classes in food products. Effective analytical techniques for detecting mycotoxins are critically important to monitor and prevent contaminated foods. Nevertheless, most current analytical techniques for mycotoxin detection require sophisticated and expensive equipment, complicate detection procedures, and high cost, which impose grand challenges for extensive implementation of mycotoxin detection in food industry. This project is committed to developing a simple, sensitive, and low-cost technique for detection of mycotoxins in foods. The technique relies on unique metallic nanoscale particles (nanoparticles) that possess enzyme-like activities. The metallic nanoparticles acting as enzyme mimics can generate intense color signal through catalysis. The color signal can be conveniently detected and quantified by an inexpensive spectrophotometer. After conjugation with biomolecules, the metallic nanoparticles can be used as colorimetric labels for sensitive detection of mycotoxins. The success of this project will be of great benefit to food and agriculture systems by offering a simple, sensitive, and affordable technique for mycotoxin detection.
Animal Health Component
0%
Research Effort Categories
Basic
100%
Applied
0%
Developmental
0%
Goals / Objectives
The over-arching goal of this project is to develop a new enzyme-linked immunosorbent assay (ELISA), which relies on enzyme mimics made of unique metallic nanoparticles as labels, for simple and sensitive detection of mycotoxins in food products. This goal will be addressed through the following three objectives: 1. Engineering the enzyme mimics made of metallic nanoparticles, which will possess maximized enzyme-like activities. The enzyme-like activities enable the nanoparticles to generate strong color signal by catalyzing chromogenic substrates; 2. Establishing the enzyme mimic-based ELISA, aiming for a substantial improvement (ideally two orders of magnitude) in detection sensitivity relative to conventional natural enzyme-based ELISA; 3. Validating the enzyme mimic-based ELISA for detection of mycotoxins in food products.
Project Methods
Approaches for accomplishing the objectives are outlined in the following. In objective 1, the enzyme mimics made of metallic nanoparticles will be synthesized using a solution-phase synthesis, where a mixture of precursors of nickel (Ni) and metal M (M = platinum, iridium, and/or palladium) will be co-reduced by a reductant in synthetic reaction solution. As-prepared nanoparticles will be characterized with various analytical tools such as electron microscopy, from which the size, shape, and elemental composition of the particles will be revealed. Enzyme-like catalytic activity of the nanoparticles will be evaluated using the steady-state kinetic assay. In objective 2, the metallic nanoparticles as enzyme mimics will be functionalized with antibodies to form nanoparticle-antibody conjugates. These conjugates will be used as labels to assemble the enzyme mimic-based ELISA. The resultant ELISA will be used to detect aflatoxin B1 and fumonisin B1 as model mycotoxins in assay buffer, from which the sensitivity, reproducibility, specificity, and stability of the assay will be determined. In objective 3, Various aflatoxin B1 and fumonisin B1 spiked food samples and reference food samples will be detected using the enzyme mimic-based ELISA. Non-specific signal of the detection will be evaluated and eliminated by optimizing assay conditions. Detection performance of the enzyme mimic-based ELISA will be evaluated by comparing it with commercially available detection techniques.