Highly Sensitive Chemiluminescence-Based Lateral Flow Immunoassay for Cardiac Troponin I Detection in Human Serum

Sensors

Gyeo-Re Han¹  Min-Gon Kim¹ 

[1] Department of Chemistry, Gwangju Institute of Science and Technology (GIST), 123 Cheomdangwagi-ro, Buk-gu, Gwangju 61005, Korea;

关键词: enzyme-based biosensor;    chemiluminescence immunoassay;    lateral flow assay;    high-sensitivity;    cardiac troponin I;   

DOI  :  10.3390/s20092593

来源: DOAJ

【 摘 要 】

Lateral flow assays (LFAs) have become the most common biosensing platforms for point-of-care testing due to their compliance with the ASSURED (affordable, sensitive, specific, user-friendly, rapid/robust, equipment-free, and deliverable to end-users) guidelines stipulated by the World Health Organization. However, the limited analytical sensitivity and low quantitative capability of conventional LFAs, which use gold nanoparticles (AuNPs) for colorimetric labeling, have prevented high-performance testing. Here, we report the development of a highly sensitive chemiluminescence (CL)-based LFA involving AuNPs conjugated with aldehyde-activated peroxidase and antibody molecules—i.e., AuNP-(ald)HRP-Ab—as a new conjugation scheme for high-performance testing in LFAs. When paired with the CL-based signal readout modality, the AuNP-(ald)HRP-Ab conjugate resulted in 110-fold enhanced sensitivity over the colorimetric response of a typical AuNP-Ab conjugate. To evaluate the performance of the CL-based LFA, we tested it with human cardiac troponin I (cTnI; a standard cardiac biomarker used to diagnose myocardial infarction) in standard and clinical serum samples. Testing the standard samples revealed a detection limit of 5.6 pg·mL⁻¹ and acceptably reliable precision (with a coefficient of variation of 2.3%–8.4%), according to clinical guidelines. Moreover, testing the clinical samples revealed a high correlation (r = 0.97) with standard biochemical analyzers, demonstrating the potential clinical utility of the CL-based LFA for high-performance cTnI testing.

【 授权许可】

Unknown