Danyang ZhangXiaolin YangPeng MingNing YangChengxiao ZhangHonglan Qi
Electrochemiluminescence immunoassay (ECLIA), recognized for its good sensitivity and selectivity, has been widely commercialized in the field of in vitro diagnostics. Despite its advancements, the determination of protein biomarkers at concentrations below pg/mL remains a significant challenge in automated ECLIA. Here, a new magnetic rolling circle amplification-assisted automated ECLIA (ECLIA-RCA) method was proposed for ultrasensitive determination of protein biomarkers. The presence of protein biomarkers could specifically drive the formation of magnetic immunocomplexes between the magnetic bead (MB)-based capture antibody, the target protein, and the single-stranded DNA-tagged secondary antibody. Subsequent triggering of the RCA reaction and signal labeling enables the hybridization of a substantial number of Ru(bpy)32+ derivative-labeled single-stranded DNA to the elongated DNA linkers attached to each magnetic immunocomplex, thereby significantly amplifying the ECL signal. By integrating RCA with MB separation, the developed ECLIA-RCA method realized sensitive determination of cardiac troponin I (cTnI) with a detection limit of 0.1 pg/mL. The method also demonstrates excellent selectivity with minimal interference from nontarget proteins. Validation using 19 clinical human serum samples revealed a good linear correlation of the measured cTnI concentrations between the ECLIA-RCA results and clinical results (R2 = 0.9471). Additionally, the versatility of this automated ECLIA-RCA approach was successfully demonstrated through the quantification of alpha-fetoprotein, achieving a detection limit of 0.3 pg/mL. The ECLIA-RCA method holds great promise for the ultrasensitive determination of protein biomarkers, offering significant potential for early disease diagnosis.
Guixiao JinChunmei WangLinlin YangXiaojuan LiLonghua GuoBin QiuZhenyu LinGuonan Chen
Jian ZhangWenshuai ZhouHonglan QiXiaowei He
Jingjing ShiChao LeiWenjiao FanYuanyuan SunChenghui Liu
Li‐Juan OuSijia LiuXia ChuGuo‐Li ShenRu‐Qin Yu
Takeo YoshimuraKunitada NishidaKeiichi UchibayashiShokichi Ohuchi