TY - JOUR
T1 - Differential-based biosensor array for fluorescence-chemometric discrimination and the quantification of subtle chloropropanols by cross-reactive serum albumin scaffolding
AU - Wong, Siew Fang
AU - Low, Kah Hin
AU - Khor, Sook Mei
N1 - Funding Information:
This work was financially supported by the Fundamental Research Grant Scheme ( FRGS ) from the Ministry of Higher Education of Malaysia ( MOHE ) ( FP035-2019A ). Besides, the authors would like to thank Associate Professor Dr. Hairul Anuar Tajuddin and Professor Dr. Saiful Anuar Karsani from the Faculty of Science for their permissions in using fluorescence spectrophotometer and microplate reader throughout this research study, respectively.
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - Food contamination is a serious concern because of a high level of chemicals in food causes severe health issues. Safeguarding the public from the risk of adulterated foods has become a challenging mission. Chloropropanols are of importance to food safety and food security because they are common chemical food contaminants and believed to be carcinogenic to humans. In chemical sensing, chloropropanols are challenging analytes owing to the lacking diversity of functional groups and difficulty in targeting the hydroxyl group in aqueous environments. Moreover, because of their small molecular size, the compositions of chloropropanols remain challenging for achieving chromatographic determination. Herein, to simulate human smell and taste sensations, serum albumins, which are protein-based receptors, were introduced as low-selective receptors for differential sensing. Utilizing serum albumins, a fluorophore (PRODAN), and an additive (ascorbic acid), a differential-based optical biosensor array was developed to detect and differentiate chloropropanols. By integrating the sensor array with linear discriminant analysis (LDA), four chloropropanols were effectively differentiated based on their isomerism properties and the number of the hydroxyl groups, even at ultra-low concentration (5 nM). This concentration is far below the maximum tolerable level of 0.18 μM for chloropropanols. The sensing array was then employed for chloropropanols differentiation and quantification in the complex mixtures (e.g., synthetic soy and dark soy sauces). Leave-one-out cross-validation (LOOCV) analysis demonstrated 100% accurate classification for all tests. These results signify our differential sensing array as a practical and powerful tool to speedily identify, differentiate, and even quantify chloropropanols in food matrices.
AB - Food contamination is a serious concern because of a high level of chemicals in food causes severe health issues. Safeguarding the public from the risk of adulterated foods has become a challenging mission. Chloropropanols are of importance to food safety and food security because they are common chemical food contaminants and believed to be carcinogenic to humans. In chemical sensing, chloropropanols are challenging analytes owing to the lacking diversity of functional groups and difficulty in targeting the hydroxyl group in aqueous environments. Moreover, because of their small molecular size, the compositions of chloropropanols remain challenging for achieving chromatographic determination. Herein, to simulate human smell and taste sensations, serum albumins, which are protein-based receptors, were introduced as low-selective receptors for differential sensing. Utilizing serum albumins, a fluorophore (PRODAN), and an additive (ascorbic acid), a differential-based optical biosensor array was developed to detect and differentiate chloropropanols. By integrating the sensor array with linear discriminant analysis (LDA), four chloropropanols were effectively differentiated based on their isomerism properties and the number of the hydroxyl groups, even at ultra-low concentration (5 nM). This concentration is far below the maximum tolerable level of 0.18 μM for chloropropanols. The sensing array was then employed for chloropropanols differentiation and quantification in the complex mixtures (e.g., synthetic soy and dark soy sauces). Leave-one-out cross-validation (LOOCV) analysis demonstrated 100% accurate classification for all tests. These results signify our differential sensing array as a practical and powerful tool to speedily identify, differentiate, and even quantify chloropropanols in food matrices.
KW - Chemometrics
KW - Chloropropanols
KW - Differential sensing
KW - Fluorescence
KW - Linear discriminant analysis
KW - Serum albumins
UR - http://www.scopus.com/inward/record.url?scp=85085255908&partnerID=8YFLogxK
U2 - 10.1016/j.talanta.2020.121169
DO - 10.1016/j.talanta.2020.121169
M3 - Article
C2 - 32797922
AN - SCOPUS:85085255908
SN - 0039-9140
VL - 218
JO - Talanta
JF - Talanta
M1 - 121169
ER -