Rapid Identification of Brucella Genus and Species In Silico and On-Site Using Novel Probes with CRISPR/Cas12a
文献类型： 外文期刊
作者： Zhang, Yan 1 ; Lyu, Yufei 2 ; Wang, Dongshu 2 ; Feng, Meijie 1 ; Shen, Sicheng 2 ; Zhu, Li 2 ; Pan, Chao 2 ; Zai, Xiaodong 2 ; Wang, Shuyi 2 ; Guo, Yan 2 ; Yu, Shujuan 2 ; Gong, Xiaowei 4 ; Chen, Qiwei 4 ; Wang, Hengliang 1 ; Wang, Yuanzhi 5 ; Liu, Xiankai 2 ;
作者机构： 1.Shanghai Ocean Univ, Coll Food Sci & Technol, 999 Hucheng Huan Rd, Shanghai 201306, Peoples R China
2.Beijing Inst Biotechnol, State Key Lab Pathogens & Biosecur, 20 Dongdajie St, Beijing 100071, Peoples R China
3.Lab Adv Biotechnol, 20 Dongdajie St, Beijing 100071, Peoples R China
4.Chinese Acad Agr Sci, State Key Lab Anim Dis Control & Prevent, Lanzhou Vet Res Inst, Lanzhou 730046, Peoples R China
5.Shihezi Univ, Sch Med, Shihezi 832002, Peoples R China
关键词： brucellosis; Brucella abortus; Brucella meltisensis; probes; detection; Cas12a
期刊名称：MICROORGANISMS （ 影响因子：4.5； 五年影响因子：4.8 ）
ISSN：
年卷期： 2024 年 12 卷 5 期
页码：
收录情况： SCI
摘要： Human brucellosis caused by Brucella is a widespread zoonosis that is prevalent in many countries globally. The high homology between members of the Brucella genus and Ochrobactrum spp. often complicates the determination of disease etiology in patients. The efficient and reliable identification and distinction of Brucella are of primary interest for both medical surveillance and outbreak purposes. A large amount of genomic data for the Brucella genus was analyzed to uncover novel probes containing single-nucleotide polymorphisms (SNPs). GAMOSCE v1.0 software was developed based on the above novel eProbes. In conjunction with clinical requirements, an RPA-Cas12a detection method was developed for the on-site determination of B. abortus and B. melitensis by fluorescence and lateral flow dipsticks (LFDs). We demonstrated the potential of these probes for rapid and accurate detection of the Brucella genus and five significant Brucella species in silico using GAMOSCE. GAMOSCE was validated on different Brucella datasets and correctly identified all Brucella strains, demonstrating a strong discrimination ability. The RPA-Cas12a detection method showed good performance in detection in clinical blood samples and veterinary isolates. We provide both in silico and on-site methods that are convenient and reliable for use in local hospitals and public health programs for the detection of brucellosis.
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