流动相单分子免疫检测系统的设计

胡鹏涛; 高若谦; 葛明锋; 董文飞; 李力; 苏新然

doi:10.37188/CO.2025-0045

流动相单分子免疫检测系统的设计

doi: 10.37188/CO.2025-0045

cstr: 32171.14.CO.2025-0045

胡鹏涛^{1, 2,},
高若谦^1, ,,
葛明锋^1,,
董文飞^{1, 2,},
李力^1,,
苏新然^{1, 2,}

1.
中国科学院苏州生物医学工程技术研究所, 江苏苏州 215163
2.
长春理工大学机电工程学院, 吉林长春 130022

基金项目: 国家重点研发计划（No. 2022YFC2403502）；吉林省与中国科学院科技合作高新技术产业化专项资金项目（No. 2023SYHZ0037）；山东省青年自然科学基金项目（No. ZR2023QF136）

详细信息

作者简介:
高若谦（1993—），男，吉林长春人，博士，2020年于中国科学院长春光学精密机械与物理研究所获得博士学位，主要从事高光谱、成像光学等方面研究。E-mail：gaorq@sibet.ac.cn

葛明锋(1987-)，男，江苏南通人，博士，研究员，硕士生导师，主要从事高光谱、荧光显微成像方面研究。E-mail：gemf@sibet.ac.cn

董文飞(1975-)，男，吉林长春人，博士，研究员，博士生导师，1999年于中国科学院长春应用化学研究所获得高分子物理化学专业硕士学位，2004年于德国马普胶体界面所和波兹坦大学获得自然科学博士学位，主要从事纳米材料和技术在生物医用光子学领域的应用基础研究。E-mail: wenfeidong@126.com

李力（1986-），男，江苏昆山人，博士，研究员，博士生导师，主要从事荧光探针及检测试剂方面研究。E-mail: lil@sibet.ac.cn

苏新然(1999-)，男，吉林松原人，硕士研究生，主要从事机械工程等方面研究。E-mail: xinransu@mails.cust.edu.cn

中图分类号: O439
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出版历程
- 收稿日期: 2025-03-14
- 修回日期: 2025-04-02
- 录用日期: 2025-04-16
- 网络出版日期: 2025-05-21

Design of flow-phase single-molecule immunoassay detection system

HU Peng-tao^{1, 2
,},
GAO Ruo-qian^{1
, ,},
GE Ming-feng^1
,,
DONG Wen-fei^{1, 2
,},
LI Li^1
,,
SU Xin-ran^{1, 2
,}

1.
Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
2.
School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130022, China

Funds: Supported by the National Key R&D Program of China (No. 2022YFC2403502); Science and Technology Cooperation Special Project, Jilin Province and Chinese Academy of Sciences (No. 2023SYHZ0037); Shandong Provincial Natural Science Foundation, China (No. ZR2023QF136)

More Information

Corresponding author: gaorq@sibet.ac.cn

摘要

摘要:
为实现肿瘤标志物的早期诊断，本文设计了一种适用于流动相样本的单分子免疫检测系统，并对其光学荧光成像平台及图像检测计数算法进行了研究。首先，为满足低浓度、高通量样本的即时检测需求，提出了一种基于流动相的单分子免疫检测方法。其次，结合微流控芯片的规格要求，设计了一套光学荧光成像检测平台，通过滤光和分光元件的合理配置，利用多模块集成实现荧光样本的高分辨率成像。最后，在离焦粒子的图像检测计数算法的基础上，优化了特征匹配方法，以高效处理非焦面荧光粒子信号。实验结果表明，本系统在单分子免疫标志物样本检测中的下限可达到0.001 pg/mL，在0.001～1 pg/mL的理论检测范围内，变异系数均小于10%，可在一小时内完成最多十份样本的检测。本系统满足了单分子免疫检测的稳定性、高灵敏度和高通量检测需求，在癌症早期筛查领域具有重要的应用前景。
- 早期诊断 /
- 单分子免疫检测 /
- 荧光成像 /
- 光学平台 /
- 特征匹配
Abstract:
We develop a single-molecule immunoassay detection system for flow-phase samples to enable early diagnosis of tumor biomarkers. The system includes an optical fluorescence imaging platform and an image processing algorithm. First, we developed a flow-phase single-molecule immunoassay detection method suitable for real-time detection of low-concentration, high-throughput samples. Second, we designed a set of fluorescence imaging detection platform compatible with microfluidic chips. Through the rational configuration of optical filters and beam splitters, high-resolution fluorescence imaging was achieved by utilizing multi-module integration. Finally, based on the image detection and counting algorithm for out-of-focus particles, we optimized a feature-matching algorithm to effectively detect out-of-focus fluorescent particles. Experimental results demonstrate a detection limit of 0.001 pg/mL within a linear range of 0.001−1 pg/mL, with coefficient of variation below 10%. The system can process up to 10 samples per hour. These findings indicate that our system meets the requirements for stable, sensitive, and high-throughput single-molecule immunoassay detection, showing promising potential for early cancer screening.
- early diagnosis /
- single-molecule immunodetection /
- fluorescence imaging /
- optical platform /
- feature matching

HTML全文

图 1 单分子免疫检测系统的构成

Figure 1. Components of the single-molecule immunoassay detection system

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图 2 单分子免疫样本与微流控芯片示意图

Figure 2. Schematic of the single-molecule immune samples integrated with a microfluidic chip

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图 3 光学荧光成像系统光路示意图

Figure 3. Optical path diagram of the fluorescence imaging system

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图 4 单分子免疫检测系统整机

Figure 4. Integrated single-molecule immunoassay detection system

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图 5 粒子成像原理示意图

Figure 5. Schematic diagram of particle imaging principle

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图 6 光学系统成像坐标系示意图

Figure 6. Schematic diagram of the optical imaging coordinate system

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图 7 互相关粒子检测算法检测流程

Figure 7. Flowchart of the cross-correlation particle detection algorithm

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图 8 单分子免疫成像检测流程图

Figure 8. Workflow of single-molecule immunoimaging detection

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图 9 系统采集的单帧图像

Figure 9. Single-frame image captured by the proposed system

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图 10 不同高度上荧光粒子的信噪比与互相关峰值

Figure 10. Signal-to-noise ratio and cross-correlation peak values of fluorescent particles at different heights

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图 11 系统训练的匹配预测模型

Figure 11. Matching prediction model trained by the proposed system

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图 12 成像检测系统检测结果

Figure 12. Detection results of the imaging detection system

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图 13 数据拟合结果

Figure 13. Data fitting results

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表 1 a样本荧光粒子检测结果

Table 1. Detection results of fluorescent particles in sample a

稀释倍率	a₁	a₂	a₃	平均值
1∶500	4.54	3.94	5.1	4.53
1∶1000	2.23	2.13	1.65	2
1∶3000	0.53	0.79	0.78	0.7
1∶4000	0.64	0.49	0.38	0.5
1∶5000	0.55	0.32	0.42	0.43
1∶10000	0.32	0.25	0.18	0.25
1∶50000	0.01	0.01	0	0.01

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表 2 b样本荧光粒子检测结果

Table 2. Detection results of fluorescent particles in sample b

稀释倍率	b₁	b₂	b₃	平均值
1∶500	4.41	4.14	3.93	4.16
1∶1000	2.09	1.37	1.56	1.67
1∶3000	0.98	0.77	0.64	0.79
1∶4000	0.46	0.43	0.4	0.43
1∶5000	0.57	0.56	0.26	0.46
1∶10000	0.24	0.31	0.17	0.24
1∶50000	0	0.01	0	0

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表 3 本文系统与Simoa HD-X系统性能对比

Table 3. Performance comparison between the proposed system and Simoa HD-X system

性能参数	Simoa系统	本系统
取样量	1～100 μL	1～100 μL
反应量	0.048 μL	0.2～1 μL
检测限	0.01～100 pg/mL	0.001～1 pg/mL
动态范围	≥4个数量级	≥3个数量级
精确度	CV<10%	CV<10%

下载: 导出CSV

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