利用微流体自适应通道和多重荧光显微镜快速鉴定细菌分离物

IF 6.1 2区 工程技术 Q1 BIOCHEMICAL RESEARCH METHODS
Lab on a Chip Pub Date : 2024-09-06 DOI:10.1039/D4LC00325J
Stelios Chatzimichail, Piers Turner, Conor Feehily, Alison Farrar, Derrick Crook, Monique Andersson, Sarah Oakley, Lucinda Barrett, Hafez El Sayyed, Jingwen Kyropoulos, Christoffer Nellåker, Nicole Stoesser and Achillefs N. Kapanidis
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引用次数: 0

摘要

我们展示了利用自适应通道细菌捕获 (ACBC) 设备快速捕获、富集和鉴定细菌病原体的方法。通过控制聚二甲基硅氧烷(PDMS)装置中装置背压的调整,我们能够控制捕获区域的形成,以接近 100% 的捕获效率从低细胞密度样本中捕获细菌。与传统的细菌捕获方法相比,制备这种装置的技术要求要低得多,而且可以通过简单的台式制造方法实现。我们演示了在细菌浓度低于 1000 cells/mL 的情况下捕获和鉴定 7 种细菌,包括常见的革兰氏阴性和革兰氏阳性病原体,如大肠杆菌和金黄色葡萄球菌。我们还进一步证明,使用多重 16S rRNA-FISH 技术可在一小时内完成被捕获细菌的物种鉴定,采用无监督分类方法对 7 种细菌的鉴定准确率可达 70-98%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Rapid identification of bacterial isolates using microfluidic adaptive channels and multiplexed fluorescence microscopy†

Rapid identification of bacterial isolates using microfluidic adaptive channels and multiplexed fluorescence microscopy†

We demonstrate the rapid capture, enrichment, and identification of bacterial pathogens using Adaptive Channel Bacterial Capture (ACBC) devices. Using controlled tuning of device backpressure in polydimethylsiloxane (PDMS) devices, we enable the controlled formation of capture regions capable of trapping bacteria from low cell density samples with near 100% capture efficiency. The technical demands to prepare such devices are much lower compared to conventional methods for bacterial trapping and can be achieved with simple benchtop fabrication methods. We demonstrate the capture and identification of seven species of bacteria with bacterial concentrations lower than 1000 cells per mL, including common Gram-negative and Gram-positive pathogens such as Escherichia coli and Staphylococcus aureus. We further demonstrate that species identification of the trapped bacteria can be undertaken in the order of one-hour using multiplexed 16S rRNA-FISH with identification accuracies of 70–98% with unsupervised classification methods across 7 species of bacteria. Finally, by using the bacterial capture capabilities of the ACBC chip with an ultra-rapid antimicrobial susceptibility testing method employing fluorescence imaging and convolutional neural network (CNN) classification, we demonstrate that we can use the ACBC chip as an imaging flow cytometer that can predict the antibiotic susceptibility of E. coli cells after identification.

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来源期刊
Lab on a Chip
Lab on a Chip 工程技术-化学综合
CiteScore
11.10
自引率
8.20%
发文量
434
审稿时长
2.6 months
期刊介绍: Lab on a Chip is the premiere journal that publishes cutting-edge research in the field of miniaturization. By their very nature, microfluidic/nanofluidic/miniaturized systems are at the intersection of disciplines, spanning fundamental research to high-end application, which is reflected by the broad readership of the journal. Lab on a Chip publishes two types of papers on original research: full-length research papers and communications. Papers should demonstrate innovations, which can come from technical advancements or applications addressing pressing needs in globally important areas. The journal also publishes Comments, Reviews, and Perspectives.
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