A Bifunctional “Two-in-One” Array for Simultaneous Diagnosis of Irritable Bowel Syndrome and Identification of Low-FODMAP Diets

Abstract

Irritable bowel syndrome (IBS) is a globally prevalent functional gastrointestinal disorder frequently misdiagnosed due to overlapping symptoms with other diseases. Currently, there are no rapid and effective diagnostic or therapeutic approaches for IBS. Despite this, low-FODMAP diets (LFDs) have become a major dietary intervention strategy for symptom relief. However, detecting FODMAPs usually relies on chromatographic techniques, which are costly and time-consuming, making it difficult to apply in real-time detection. In this study, we introduce the first dual-functional sensor array capable of rapidly diagnosing IBS and identifying low-FODMAP diets. This six-element array was constructed using nitrophenylboronic acid-modified poly(ethylenimine) coupled with coumarins through dynamic borate ester bonds across a range of pH conditions. Optimized by diverse machine learning algorithms, with the multilayer perceptron (MLP) algorithm proving optimal, the array enabled the simultaneous identification of 12 intestinal bacteria with 99.2% accuracy and the detection of mouse fecal specimens with varying degrees of IBS with 99.8% accuracy within seconds. Furthermore, it allowed for the detection of various FODMAP levels in commercially purchased, brand-named, and differently processed soy milk. The array demonstrates potential for use in both the clinical diagnosis of IBS and the guiding of low-FODMAP diets for patients.