AMPLIFICATION-BY-POLYMERIZATION IN BIOSENSING FOR VISUAL DETECTION OF PEANUT ALLERGENS

  • He, P. P. (Investigador principal)

Detalles del proyecto

Descripción

Food allergy becomes a food safety issue due to abnormal immune responses to food accompanied with mild to severe symptoms.1 peanut allergy is one of the most prevalent, long-lasting, and severe food allergies caused by a type i hypersensitivity reaction to immune system.2,3 peanut allergy commonly causes food-induced anaphylaxis (fia) in developed countries. currently, in the united states 2.5% of children and 1.8% of adults are allergic to peanut,4,5 more than double from ten years ago.6 a typical immunoglobulin e (ige)-mediate type i hypersensitivity is triggered by allergenic proteins in peanuts or in foods containing peanuts.7 up to 75% of individuals with known peanut allergy experience anaphylactic reactions caused by accidental exposure. so far, the most popular allergen detection method is enzyme-linked immunosorbent assay (elisa), which relies on a specific antibody to bind to the target antigen analyte.8 the elisa kits are utilized to quantify individual peanut allergen or to determine total peanut allergenic proteins in a food matrix depending on whether monoclonal or polyclonal primary antibody is used. although elisa has been a widely adopted method with strong specificity, expensive bioreagents (antibodies, enzymes, tags, etc.) and the time-consuming and laboring process required by elisa have limited its applications in timely peanut allergen detection for individuals with peanut allergy. gel electrophoresis and lc/ms are confirmatory alternatives for food allergen detection,9 but they are non-portable, as time-consuming as elisa, and expensive. another method for peanut allergen quantification is rp-hplc with detection range of 25-400 µg/ml which is significantly less sensitive than elisa and gel electrophoresis.10 the challenge nowadays in peanut allergen detection therefore lies in simplifying detection process and building rapid and cost-effective sensors that are amenable to point-of-need applications without compromising achieved sensing sensitivity.the proposed research team consists of dr. peng he (pi) and his research group in north carolina agricultural and technical state university (ncat) chemistry and dr. jianmei yu (co-pi) and her group in ncat food science. research in the he lab focuses on developing new bioanalytical methodologies to address current challenges in the field of biosensing. the efforts include the developments of new types of polymer/polymerization-based biosensing techniques. dr. yu is a well-known food scientist for her peanut allergen research with groundbreaking work 'devised a process that removes 98 percent of the major allergens in roasted peanuts using a naturally occurring enzyme' highlighted by the supporters of agricultural research (soar) foundation. the long-term goal of this proposed collaborative research is to develop a biosensing-based, simple, robust, inexpensive, rapid, and sensitive peanut allergen detection platform to protect individuals with peanut allergy from accidental/unintentional exposure. this platform uses real-time molecular growth via an amplification-by-polymerization (abp) process to achieve label-free and detector-free allergenic protein detection. the proposed research will be conducted by accomplishing two supporting objectives: (1) proof-of-concept of peanut allergenic protein detection using reversible-deactivation radical polymerizations and (2) sensitivity, specificity, and accuracy optimizations for the developed biosensing method validation, performance comparison with commercially available elisa kits, and further development into a multiplexed bioassay.
EstadoActivo
Fecha de inicio/Fecha fin1/9/2131/8/24

Financiación

  • National Institute of Food and Agriculture: USD200,000.00

!!!ASJC Scopus Subject Areas

  • Inmunología
  • Polímeros y plásticos
  • Inmulogía y alergología
  • Agricultura y biología (todo)
  • Química (todo)

Huella digital

Explore los temas de investigación que se abordan en este proyecto. Estas etiquetas se generan con base en las adjudicaciones/concesiones subyacentes. Juntos, forma una huella digital única.