Mixing of pH indicators and ninhydrin to fabricate artificial tasting devices for discrimination of amino acids: A comparison between liquid- and solid-supported analytical devices and application to identification of bladder cancer

Abstract

Amino acids (AAs) are essential elements for protein formation and are associated with various health conditions. Therefore, identifying and determining AAs in biological fluids can facilitate the development of straightforward methods for disease detection. This paper discusses a novel colorimetric sensor array platform that utilizes mixtures of pH indicators and ninhydrin. Identification and discrimination of AAs in biological fluids, following by rapid detection of bladder cancer was achieved by this simple sensing system. The sensor array, mimicking the gustatory systems of mammalians, was fabricated using both liquid- and solid-supports. Consequently, the effect of support on the selectivity of the sensor array was investigated. Statistical analyses of the data by linear discriminate analysis (LDA) and random forest (RF) resulted in discriminant models with accuracies of 96% and 100% for the classification of all 20 natural AAs. Additionally, the sensitivity and specificity for liquid-supports were 96% and 99.8%, while for solid-supports, they were 93% and 99.7%, respectively. As a proof of concept, the sensor arrays were used as untargeted metabolomics tools to identify bladder cancer using urine samples. Both liquid- and solid-supported optical tongue devices successfully discriminated the urine samples of cancerous individuals from the healthy ones.