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Published on: October 10, 2013
Poly(amino acid) Dot-Based Fluorescent Receptor Array for Multiplexed Sensing of Saccharides and Amino Acids
Yue Yang1, Meilin Wu1, Quan Li1
1College of Chemistry and Chemical Engineering, Chongqing University, Chongqing400000, China.
Abstract:
Inspired by protein-based odorant recognition in the mammalian olfactory system, we constructed a biomimetic fluorescent sensor array using poly(amino acid) dots synthesized from tyrosine, alanine, and cysteine. Saccharides and amino acids are two categories of structurally analogous small molecules that coexist widely in biological and food matrices (e.g., energy drinks, nutritional supplements, fermented products). Their simultaneous monitoring is challenging because of their completely different functional groups. While most studies target individual detection of such organic compounds, rapid methods capable of simultaneously detecting saccharides and amino acids in a multiplexed manner remain scarce. Here, we designed a multidimensional fluorescence sensor array in which the poly(amino acid) dots act as receptors, zinc ion and pH serve as modulators, and four excitation wavelengths (320, 370, 420, and 470 nm) are introduced as independent information channels that provide additional response dimensions. Unlike conventional arrays that rely on increasing the number of physical sensors, this strategy treats each excitation wavelength as an independent response channel, quadrupling the data points per sensor (16 output channels from 4 physical sensors) while substantially simplifying array construction. Combined with machine learning algorithms (PCA, OPLS-DA, PLSR, and SVM), the array correctly identified ten small molecules from the two categorized groups (saccharides and amino acids) with 100% recognition accuracy. Quantitative detection of fructose, valine, and glutamic acid was achieved with limits of detection (LODs) of 0.032, 0.11, and 0.078 μg/mL, respectively. The array also successfully discriminated ternary mixtures of these analytes and, when applied to real samples (orange soda and green tea), showed excellent agreement with standard HPLC methods. This multidimensional approach holds great potential for rapid multiplex sensing in medical diagnostics, food quality control, and environmental monitoring.
