An inherently kidney-targeting near-infrared fluorophore based probe for early detection of acute kidney injury

急性肾损伤 荧光团 医学 过氧亚硝酸盐 肾脏疾病 生物标志物 病理 药理学 化学 内科学 荧光 生物化学 超氧化物 物理 量子力学
作者
Fangqin Wang,Xuefeng Jiang,Huaijiang Xiang,Ning Wang,Yunjing Zhang,Xi Yao,Ping Wang,Hao Pan,Li-Fang Yu,Yunfeng Cheng,Yongzhou Hu,Weiqiang Lin,Xin Li
出处
期刊:Biosensors and Bioelectronics [Elsevier]
卷期号:172: 112756-112756 被引量:32
标识
DOI:10.1016/j.bios.2020.112756
摘要

Acute kidney injury (AKI) is common in hospital patients. Delayed diagnosis and treatment of AKI due to the lack of efficient early diagnosis is an important cause of its high mortality. While fluorescence imaging seems promising to non-intrusively interrogate AKI-related biomarkers, the low kidney contrast of many fluorophores conferred by their relatively low abundance of distribution in the kidney limits their application for AKI detection. Herein, we discovered a near-infrared fluorophore with inherent kidney-targeting ability. Based on this fluorophore, a fluorogenic probe (KNP-1) was developed by targeting peroxynitrite (ONOO−), which is upregulated at the early onset of AKI. KNP-1 exhibits desirable kidney distribution after intravenous administration and is fluorescent only after activation by ONOO−. These properties lead to excellent kidney contrast imaging results. KNP-1 is capable of detecting both nephrotoxin-induced and ischemia-reperfusion injury-induced AKI in live mice. Temporally resolved imaging of AKI-disease model mice with KNP-1 suggests a gradual increase in renal ONOO− levels with disease progression. Notably, the upregulation of ONOO− can be observed at least 24 h earlier than the clinically popular sCr and BUN methods. Blocking ONOO− generation also proves beneficial. These results highlight the applicability of this inherently tissue targeting-based strategy for designing probes with desirable imaging contrast; potentiate ONOO− as a biomarker and target for AKI early diagnosis and medical intervention; and imply the clinical relevance of KNP-1 for AKI early detection.
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