Journal
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
Volume 66, Issue 11, Pages 3003-3008Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jafc.7b05289
Keywords
norovirus; PCR; G-quadruplex; shellfish; colorimetric sensor
Funding
- World Institute of Kimchi - Ministry of Science, Information and Communications Technology (ICT) and Future Planning, Republic of Korea [KE1701-5]
- Gwangju Institute of Science and Technololgy (GIST), Republic of Korea, under the Practical Research and Development support program
Ask authors/readers for more resources
Worldwide, norovirus is one of the most associated causes of acute gastroenteritis, which leads to nearly 50 000 child deaths every year in developing countries. Therefore, there is great demand to develop a rapid, low-cost, and accurate detection assay for the foodborne norovirus infection to reduce mortality caused by norovirus. Considering the importance of norovirus, we have demonstrated a highly sensitive and specific colorimetric detection method for analysis of human norovirus genogroups I and II (HuNoV GI and GII) in oyster samples. This is the first report to employ colorimetric HRPzyme-integrated polymerase chain reaction (PCR) for direct norovirus detection from the real shellfish samples. We found that the HRPzyme-integrated PCR method is more sensitive than the gel electrophoresis approach and could detect the HuNoV GI and GII genome up to 1 copy/mL. The specificity of the proposed method was successfully demonstrated for HuNoV GI and GII. Further, we performed testing HuNoVs in the spiked oyster samples, and the HRPzyme-integrated PCR method proved to be an ultrasensitive and selective method for detecting HuNoVs in the real samples. By integration of the proposed method with the portable PCR machine, it would be more reliable to improve food safety by detecting HuNoVs in the different types of shellfish, such as oyster and mussel, at the production field.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available