重组酶聚合酶扩增
人型支原体
重组酶
病毒学
聚合酶链反应
多重位移放大
分子生物学
生物
支原体
微生物学
遗传学
基因
DNA提取
重组
作者
Xiaoying Chen,Yichao Wang,Jie Zhu,Tong Zhu,Hehui Yang,Leilei Miao,Jia-Jia Xu,Fengxiang Xi,Pan Wang,Tianjun Jia,Zhaoyun Li
出处
期刊:Clinical Laboratory
[Clinical Laboratory Publications]
日期:2021-01-01
卷期号:67 (04/2021)
被引量:2
标识
DOI:10.7754/clin.lab.2020.200826
摘要
Background Mycoplasma hominis (MH) is an opportunistic pathogen, which often causes funisitis, spontaneous abortion, and low birth weight. However, current laboratory methods are time-consuming, labor-intensive, or require specialized laboratory instruments. Recombinase polymerase amplification (RPA) technology is a rapidly developing field because of the significance for clinical application and commercial value. Few studies have reported the use of RPA to detect MH. In this study, we developed the rapid MH detection assay, which may be potentially used as a sensitive point-of-care testing (POCT) in clinic. Methods Primers based on the MH 16SrRNA gene and gap gene were explored and screened out. The probe of RPA-LFD was designed based on the optimal primer and confirmed. The reaction conditions of temperature and time for RPA were optimized. The sensitivity and specificity of the analysis were explored. A total of 60 clinical specimens were used to verify the efficiency of the two methods. Results The optimal reaction conditions were determined as 15 minutes and 39°C. The sensitivity of RPA was 10-6 ng for MH, which is 100,000 times more sensitive than traditional PCR. Moreover, we observed another six non-target reproductive tract common pathogens without amplification products. Furthermore, we found that there was no significant difference between RPA and the cultivation method (p > 0.05). These two methods were in good agreement (κ = 0.938) when detecting clinical specimens. Conclusions A new method for sensitive and rapid detection of MH based on RPA was successfully developed, which can be applied in large-scale screening and as a supplementary method to classical methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI