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基于智能手机的自发荧光成像技术检测实验室表面的细菌种类。

Smartphone-based autofluorescence imaging to detect bacterial species on laboratory surfaces.

机构信息

Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, USA.

出版信息

Analyst. 2022 Jun 27;147(13):2980-2987. doi: 10.1039/d2an00358a.

Abstract

The potential of bacterial contamination is commonly seen in biological and clinical laboratory surfaces, creating a need to detect the presence of bacteria on a surface. Various bacterial species have been found to naturally exist on surfaces, including , Typhimurium, and that were investigated in this study. Bacterial presence was identified from laboratory surfaces using a smartphone and low-cost components without culturing or staining. Autofluorescence from bacteria was quantified using a 405 nm LED as an excitation light source. A low-cost acrylic film could isolate the autofluorescence emission. ImageJ was used to process and analyze the images and quantify the emitted autofluorescence signal. This imaging platform successfully detected the presence of all three bacterial species from the heavily used laboratory surfaces. A trend of decreasing fluorescence signal was observed with decreasing bacterial concentration, and the limit of detection was 10 CFU cm. It could also distinguish from tap water, protein (bovine serum albumin), and NaCl solutions. This preliminary work emphasizes the ability to detect autofluorescence signals of bacteria and non-microbial surface contaminants using a cost-effective and straightforward imaging platform.

摘要

生物和临床实验室表面通常存在细菌污染的可能性,因此需要检测表面是否存在细菌。本研究调查了在表面自然存在的各种细菌,包括大肠杆菌、鼠伤寒沙门氏菌和金黄色葡萄球菌。使用智能手机和低成本组件在不进行培养或染色的情况下从实验室表面识别细菌的存在。使用 405nm LED 作为激发光源对细菌的自发荧光进行定量。低成本的亚克力薄膜可以隔离自发荧光发射。使用 ImageJ 处理和分析图像并量化发射的自发荧光信号。该成像平台成功地从使用频繁的实验室表面检测到了所有三种细菌的存在。随着细菌浓度的降低,荧光信号呈下降趋势,检测限为 10 CFU cm。它还可以与自来水、蛋白质(牛血清白蛋白)和 NaCl 溶液区分开来。这项初步工作强调了使用经济高效且简单的成像平台检测细菌和非微生物表面污染物自发荧光信号的能力。

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