Guan Zhen, Sun Yunze, He Yingdi, Cao Jianing, Tian Jie, Ji Zhouxiang
School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China.
School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China; Engineering Research Center of Molecular & Neuroimaging, Ministry of Education, Xidian University, Xi'an, Shaanxi, 710126, China.
Biosens Bioelectron. 2025 Nov 15;288:117752. doi: 10.1016/j.bios.2025.117752. Epub 2025 Jul 3.
Diabetic kidney disease (DKD) is a serious complication of diabetes patients with long time duration, presenting with albuminuria and/or a reduced estimated glomerular filtration rate (eGFR), and without symptoms of other primary causes of kidney injury. Clinical studies showed matrix metalloproteinase 2 (MMP2) is the potential indicator for DKD diagnosis. However, the typical measurement of MMP2 is complicated and time-consuming. Therefore, it is necessary to develop an easy and reliable approach for MMP2 detection. Herein, we proposed a reliable and easy-to-use nanopore solution for the quantitative measurement of MMP2 at the single-molecule level using α-hemolysin nanopore. Assisted by machine learning, the peptide substrate and peptide products digested by MMP2 were classified with 100 % accuracy. The quantitative range of MMP2 concentration was 50-400 ng/ml. We further investigated the inhibitory effects of MMP2 activity by different chemicals including Cu, Ni, Zn, EDTA, and its inhibitor GM6001. Finally, MMP2 measurement was explored in the presence of simulated urine. Our research provides a new solution of quantification of MMP2 activity combined with machine learning for DKD diagnosis.
糖尿病肾病（DKD）是糖尿病患者长期患病后的一种严重并发症，表现为蛋白尿和/或估算肾小球滤过率（eGFR）降低，且无其他原发性肾损伤原因的症状。临床研究表明，基质金属蛋白酶2（MMP2）是DKD诊断的潜在指标。然而，MMP2的典型检测方法复杂且耗时。因此，有必要开发一种简便可靠的MMP2检测方法。在此，我们提出了一种可靠且易于使用的纳米孔解决方案，用于使用α-溶血素纳米孔在单分子水平定量测量MMP2。在机器学习的辅助下，MMP2消化的肽底物和肽产物分类准确率达100%。MMP2浓度的定量范围为50 - 400 ng/ml。我们进一步研究了包括铜、镍、锌、乙二胺四乙酸（EDTA）及其抑制剂GM6001在内的不同化学物质对MMP2活性的抑制作用。最后，在模拟尿液存在的情况下探索了MMP2的检测。我们的研究为DKD诊断提供了一种结合机器学习定量MMP2活性的新解决方案。
