Urchin-Shaped Au–Ag@Pt Sensor Integrated Lateral Flow Immunoassay for Multimodal Detection and Specific Discrimination of Clinical Multiple Bacterial Infections

化学 检出限 色谱法 细菌 金黄色葡萄球菌 免疫分析 抗体 生物 遗传学 免疫学
作者
Xueqin Huang,Lingzhi Chen,Weixia Zhi,Runmin Zeng,Guanxu Ji,Huaihong Cai,Jun Xu,Jinyong Wang,Shanze Chen,Yong Tang,Jianglin Zhang,Haibo Zhou,Pinghua Sun
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (35): 13101-13112 被引量:101
标识
DOI:10.1021/acs.analchem.3c01631
摘要

A new lateral flow immunoassay strip (LFIA) combining sensitive detection and identification of multiple bacteria remains a huge challenge. In this study, we first developed multifunctional urchin-shaped Au-Ag@Pt nanoparticles (UAA@P NPs) with a unique combination of colorimetric-SERS-photothermal-catalytic (CM/SERS/PT/CL) properties and integrated them with LFIA for multiplexed detection and specific discrimination of pathogenic bacteria in blood samples. Unlike the conventional LFIA that relied on antibody (Ab), this novel LFIA introduced 4-mercaptophenylboronic acid (4-MPBA) as an ideal Ab replacer that was functionalized on UAA@P NPs (UAA@P/M NPs) with outstanding binding and enrichment capacities toward bacteria. Taking Staphylococcus aureus (S. aureus) as model bacteria, the limit of detection (LOD) was 3 CFU/mL for SERS-LFIA, 27 CFU/mL for PT-LFIA, and 18 CFU/mL for CL-LFIA, three of which were over 330-fold, 37-fold, and 55-fold more sensitive than ordinary visual CM-LFIA, respectively. Besides, this SERS-LFIA is capable of identifying three types of bacterial spiked blood samples (E. coli, S. aureus, and P. aeruginosa) effectively according to specific bacterial Raman "fingerprints" by partial least-squares-discriminant analysis (PLS-DA). More importantly, this LFIA was successfully applied to blood samples with satisfactory recoveries from 90.3% to 108.8% and capable of identifying the infected patients (N = 4) from healthy subjects (N = 2) with great accuracy. Overall, the multimodal LFIA incorporates bacteria discrimination and quantitative detection, offering an avenue for early warning and diagnosis of bacterial infection.
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