TY - JOUR
T1 - A Novel LC-MS Based Targeted Metabolomic Approach to Study the Biomarkers of Food Intake
AU - Tang, Yao
AU - Zhu, Yingdong
AU - Sang, Shengmin
N1 - Publisher Copyright:
© 2020 Wiley-VCH GmbH
PY - 2020/11
Y1 - 2020/11
N2 - Scope: In this work, an integrated strategy is developed for rapid discovery, precise identification, and automated quantification for the biomarkers of food intake (BFIs) for specific food exposure using an ultra-high-pressure liquid chromatography-high-resolution mass spectrometry (MS) based targeted metabolomics approach. Methods and results: Using whole grain (WG) wheat intake as an example, the combination of paired mass distance networking and parallel reaction monitoring analysis is applied to selectively extract and identify WG metabolites in human urine samples. As a result, a total of 76 wheat phytochemical-derived metabolites, including 17 alkylresorcinol metabolites, 20 benzoxazinoid derivatives, and 39 phenolic acid metabolites are identified. Subsequently, a MS spectral database consisting of the identified metabolites is created by mzVault. The characteristics of identified metabolites from the database are incorporated into the TraceFinder software to establish a quantification platform. Using a standardized urine sample, the authors are able to simultaneously quantify both free and conjugated (sulfate and glucuronide) WG wheat metabolites in real samples without further enzymatic hydrolysis, which is validated by using authentic standards to quantify these metabolites. Conclusion: This novel strategy opens the window to study the biomarkers of specific food intake and make it feasible to validate the BFIs in large-scale human studies.
AB - Scope: In this work, an integrated strategy is developed for rapid discovery, precise identification, and automated quantification for the biomarkers of food intake (BFIs) for specific food exposure using an ultra-high-pressure liquid chromatography-high-resolution mass spectrometry (MS) based targeted metabolomics approach. Methods and results: Using whole grain (WG) wheat intake as an example, the combination of paired mass distance networking and parallel reaction monitoring analysis is applied to selectively extract and identify WG metabolites in human urine samples. As a result, a total of 76 wheat phytochemical-derived metabolites, including 17 alkylresorcinol metabolites, 20 benzoxazinoid derivatives, and 39 phenolic acid metabolites are identified. Subsequently, a MS spectral database consisting of the identified metabolites is created by mzVault. The characteristics of identified metabolites from the database are incorporated into the TraceFinder software to establish a quantification platform. Using a standardized urine sample, the authors are able to simultaneously quantify both free and conjugated (sulfate and glucuronide) WG wheat metabolites in real samples without further enzymatic hydrolysis, which is validated by using authentic standards to quantify these metabolites. Conclusion: This novel strategy opens the window to study the biomarkers of specific food intake and make it feasible to validate the BFIs in large-scale human studies.
KW - dietary metabolite database
KW - food intake biomarkers
KW - paired mass distance networking
KW - targeted metabolomics
KW - whole grain wheat metabolites
UR - https://www.scopus.com/pages/publications/85092307762
U2 - 10.1002/mnfr.202000615
DO - 10.1002/mnfr.202000615
M3 - Article
SN - 1613-4125
VL - 64
JO - Molecular Nutrition and Food Research
JF - Molecular Nutrition and Food Research
IS - 22
M1 - 2000615
ER -