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Rapid Bacteriophage Quantification by Digital Biosensing on a SlipChip Microfluidic Device

噬菌体 噬菌体疗法 细菌 微流控 数字聚合酶链反应 纳米技术 抗菌剂 生物传感器 化学 重复性 微生物学 色谱法 计算生物学 生物 材料科学 生物化学 大肠杆菌 聚合酶链反应 遗传学 基因
作者
Xiang Li,Qixin Hu,Xu Liu,Jianfang Liu,Nannan Wu,Feng Shen
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (22): 8632-8639 被引量:8
标识
DOI:10.1021/acs.analchem.3c01066
摘要

The rise of antimicrobial resistance (AMR) is a major global public health concern, and it is urgent to develop new antimicrobial drugs and alternative therapies. There has been growing interest in the use of phage therapy as an alternative to treat AMR, and it has shown promising results in early studies and clinical trials. Phage quantification is a crucial step in the development and application of phage therapy. The traditional double-layer plaque assay requires cumbersome manual operations and typically takes up to 18 h to yield a rough phage estimation. Spectrophotometry, flow cytometry, and PCR-based methods cannot distinguish between infectious and noninfectious phages. Here, we developed a digital biosensing method for rapid bacteriophage quantification on a digital phage SlipChip (dp-SlipChip) microfluidic device containing 2304 microdroplets in 3 nL. By compartmentalizing the phages and bacteria in nanoliter droplets and analyzing the growth profile of bacteria at 3 h, the number of infectious phages can be precisely quantified. The results from the dp-SlipChip were consistent with the traditional double-layer plaque assay method and exhibited higher consistency and repeatability. The dp-SlipChip does not require a complex fluidic handling instrument to generate and manipulate droplets. This SlipChip-based digital biosensing method not only provides a promising tool for rapid phage quantification, which is important for the use of phages in clinical practice to treat antimicrobial-resistant bacteria, but can also be used as an ultrasensitive, high-specificity method to detect bacteria. Furthermore, this approach can be applied to other digital biology studies that require analysis at the single-object level.
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