Visual and rapid detection of Acinetobacter baumannii by a multiple cross displacement amplification combined with nanoparticles-based biosensor assay

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作者
Xueqin Cheng
Jing Yang
Meifang Wang
Peng Wu
Qiong Du
Jinjuan He
Yijun Tang
机构
[1] Taihe Hospital,Department of Respiratory and Critical Medical
[2] Hubei University of Medicine,Department of Clinical Laboratory
[3] Taihe Hospital,Department of Pharmacy
[4] Hubei University of Medicine,undefined
[5] Wuhan General Hospital of the Chinese People’s Liberation Army,undefined
来源
AMB Express | / 9卷
关键词
Multiple cross displacement amplification; Lateral flow biosensor; MCDA-LFB; Detection limit;
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学科分类号
摘要
The traditional microbiological methods used for detecting Acinetobacter baumannii were usually time-consuming and labor-intensive. Thus, we sought to establish a novel rapid detecting method for target pathogen. A set of multiple cross displacement amplification (MCDA) primers was designed to recognize 10 different regions of the pgaD gene, which was conservative and specific for the bacterium. In the MCDA system, amplification primers D1 and R1 were 5′-labeled with FITC (fluorescein) and biotin, respectively. Numerous FITC- and biotin-attached duplex amplicons were formed during the amplification stage, which were detected by nanoparticles-based lateral flow biosensors (LFB) through immunoreactions (FITC on the duplex and anti-FITC on the LFB test line) and biotin/streptavidin interaction (biotin on the duplex and streptavidin on the nanoparticles). The results showed that the optimized reaction condition of MCDA-LFB method was 62 °C within 25 min. There was no cross reaction with non-A. baumannii species and the non-Acinetobacter genera, and the detection limit for DNA samples was 100 fg/reaction. For 135 sputum samples, the detection results showed that the detection ability of MCDA-LFB assay was superior to the culture methods and conventional PCR. Therefore, MCDA-LFB assay could be a potential tool for the rapid detection of A. baumannii in clinical samples and low resource areas.
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