2022

Nanoglycocluster based diagnostic platform for colorimetric detection of bacteria; A comparative study analysing the effect of AuNPs size, linker length, and glycan diversity.

Biosensors & bioelectronics Priyadarshi N, Ambule MD, Kaushal S, Kumar A, Sagar P, Srivastava AK, Singhal NK
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组成图示

示意图生成中

传感器类型

检测对象

检测原理

检测灵敏度

效应效果

传感器的构成

中文摘要

英文摘要

Nanoglycoclusters, an upcoming class of functional nanomaterial are known to drive various processes like detection, imaging, targeting proteins, cells, and bacteria. Nanoglycoclusters are a type of nanomaterial functionalized with various glycans. The array of glycan in multiple copies enhances binding affinity with proteins. Selective and sensitive bacteria/lectin interactions using nanomaterials are an emerging area of research. The measurement of different ligand receptor interactions require sophisticated analytical tools that limit the application in biosensor domain. Recently, colorimetric biosensors gained importance in the field of the biosensor for the detection of bacteria/lectins. Herein we have demonstrated that different size of gold nanoparticles (AuNPs) along with various polyethylene glycol (PEG) linkers, functionalized with synthesized monopod and tripod of mannose and galactose that have different bacteria/lectins specificity. The newly synthesized nanoglycoclusters were able to discriminate between different lectins and bacteria. The aggregation of specific nanoglycocluster upon interaction with specific bacteria/lectins revealed that mannose monopod (MM) and mannose tripod (MT) are specific to Escherichia coli and concanavalin A (ConA) lectin, while galactose monopod (GM) and galactose tripod (GT) are specific to Pseudomonas aeruginosa and Peanut agglutinin (PNA) lectin. Further, the binding events depict the affinity of tripod glycans is more with respect to its corresponding monopod glycans. Our findings explored the potential of colorimetric sensing depending upon the size of AuNPs, linker length, specificity, along with glycans density to develop user friendly diagnostic system for the detection of bacteria.

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