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鞘层增强的极低浓度水平细菌浓缩及芯片上检测

Sheath-enhanced concentration and on-chip detection of bacteria from an extremely low-concentration level.

作者信息

Chen Xinye, Peng Ruonan, Wang Ruo-Qian, Du Ke

机构信息

Department of Chemical and Environmental Engineering, University of California, Riverside, Riverside, CA 92507, USA.

Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, New Brunswick, NJ 08854, USA.

出版信息

Lab Chip. 2025 Apr 29;25(9):2157-2167. doi: 10.1039/d4lc00698d.

DOI:10.1039/d4lc00698d
PMID:39688032
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12261496/
Abstract

Microfluidic-based sheath flow focusing methods have been widely used for efficiently isolating, concentrating, and detecting pathogenic bacteria for various biomedical applications due to their enhanced sensitivity and exceptional integration. However, such a microfluidic device usually needs complicated device fabrication and sample dilution, hampering the efficient and sensitive identification of target bacteria. In this study, we develop and fabricate a sheath-assisted and pneumatic-induced nano-sieve device for achieving the improved on-chip concentration and sensitive detection of (MRSA). The optimized nanochannel design with diverging configuration is beneficial to the regulation of the hydrodynamic flow while the sheath flow is focusing the sample to the confined region as expected. Per the experimental finding, a high flow ratio (sheath flow/sample flow) presents enhanced target concentration by comparing with a low flow ratio. With this setup, MRSA bacteria with an extremely low concentration of ∼100 CFU mL are successfully and sensitively detected under a fluorescence microscope, less than 30 min, demonstrating a reliable sheath-enhanced concentration and on-chip detection for target bacteria. Additionally, the theoretical model introduced here further rationalizes the working principle of our nano-sieve device, potentially guiding the optimization of next generation devices for highly sensitive and accurate on-chip bacteria detection at a much lower concentration level below 100 CFU mL.

摘要

基于微流控的鞘流聚焦方法因其增强的灵敏度和出色的集成性,已被广泛用于各种生物医学应用中,以高效地分离、浓缩和检测病原菌。然而,这种微流控设备通常需要复杂的设备制造和样品稀释,这阻碍了对目标细菌的高效和灵敏识别。在本研究中,我们开发并制造了一种鞘层辅助和气动诱导的纳米筛装置,用于实现对耐甲氧西林金黄色葡萄球菌(MRSA)的芯片上浓度提高和灵敏检测。具有发散配置的优化纳米通道设计有利于调节流体动力流,同时鞘流按预期将样品聚焦到受限区域。根据实验结果,与低流速比相比,高流速比(鞘流/样品流)可提高目标浓度。通过这种设置,在荧光显微镜下不到30分钟就能成功且灵敏地检测到浓度极低(约100 CFU/mL)的MRSA细菌,证明了对目标细菌可靠的鞘层增强浓缩和芯片上检测。此外,这里引入的理论模型进一步阐明了我们纳米筛装置的工作原理,有可能指导下一代设备的优化,以便在远低于100 CFU/mL的更低浓度水平上进行高灵敏度和准确的芯片上细菌检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/06ad09fa3f75/nihms-2092604-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/3607b67278fa/nihms-2092604-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/4ab7ce7aabd1/nihms-2092604-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/f53debfe4e54/nihms-2092604-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/8c6cd99162b8/nihms-2092604-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/06ad09fa3f75/nihms-2092604-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/3607b67278fa/nihms-2092604-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/4ab7ce7aabd1/nihms-2092604-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/f53debfe4e54/nihms-2092604-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/8c6cd99162b8/nihms-2092604-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a0/12261496/06ad09fa3f75/nihms-2092604-f0005.jpg

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本文引用的文献

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Pneumatic nano-sieve for CRISPR-based detection of drug-resistant bacteria.基于 CRISPR 的耐药菌检测用气动纳米筛
Nanoscale Horiz. 2023 Nov 20;8(12):1677-1685. doi: 10.1039/d3nh00365e.
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Inertial Separation of Particles Assisted by Symmetrical Sheath Flows in a Straight Microchannel.直微通道中对称鞘流辅助的颗粒惯性分离
Anal Chem. 2023 Jul 25;95(29):11132-11140. doi: 10.1021/acs.analchem.3c02089. Epub 2023 Jul 16.
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Hybrid Biomimetic Membrane Coated Particles-Mediated Bacterial Ferroptosis for Acute MRSA Pneumonia.杂化仿生膜涂层颗粒介导的急性耐甲氧西林金黄色葡萄球菌肺炎的细菌铁死亡。
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Erratum for Ma et al., "Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging".马等人的《利用人工智能和光学成像加速食品中细菌的检测》勘误
Appl Environ Microbiol. 2023 May 31;89(5):e0064423. doi: 10.1128/aem.00644-23. Epub 2023 May 8.
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Flow cytometry-based rapid detection of and using fluorescent antibodies.基于流式细胞术,使用荧光抗体快速检测……以及…… (原文中“and”前后内容缺失)
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