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通过重组酶聚合酶扩增进行特定生物标志物挖掘及复合物的快速检测。

Specific biomarker mining and rapid detection of complex by recombinase polymerase amplification.

作者信息

Fan Yiling, Wang Shujuan, Song Minghui, Zhou Liangliang, Liu Chengzhi, Yang Yan, Yu Shuijing, Yang Meicheng

机构信息

China State Institute of Pharmaceutical Industry, Shanghai, China.

National Medical Products Administration Key Laboratory for Testing Technology of Pharmaceutical Microbiology, Shanghai Quality Inspection and Testing Center for Innovative Biological Products, Shanghai Institute for Food and Drug Control, Shanghai, China.

出版信息

Front Microbiol. 2023 Sep 14;14:1270760. doi: 10.3389/fmicb.2023.1270760. eCollection 2023.

Abstract

OBJECTIVE

To mine specific proteins and their protein-coding genes as suitable molecular biomarkers for the Complex (BCC) bacteria detection based on mega analysis of microbial proteomic and genomic data comparisons and to develop a real-time recombinase polymerase amplification (rt-RPA) assay for rapid isothermal screening for pharmaceutical and personal care products.

METHODS

We constructed an automatic screening framework based on Python to compare the microbial proteomes of 78 BCC strains and 263 non-BCC strains to identify BCC-specific protein sequences. In addition, the specific protein-coding gene and its core DNA sequence were validated with a self-built genome database containing 158 thousand bacteria. The appropriate methodology for BCC detection using rt-RPA was evaluated by 58 strains in pure culture and 33 batches of artificially contaminated pharmaceutical and personal care products.

RESULTS

We identified the protein SecY and its protein-coding gene through the automatic comparison framework. The virtual evaluation of the conserved region of gene showed more than 99.8% specificity from the genome database, and it can distinguish all known BCC species from other bacteria by phylogenetic analysis. Furthermore, the detection limit of the rt-RPA assay targeting the gene was 5.6 × 10 CFU of BCC bacteria in pure culture or 1.2 pg of BCC bacteria genomic DNA within 30 min. It was validated to detect <1 CFU/portion of BCC bacteria from artificially contaminated samples after a pre-enrichment process. The relative trueness and sensitivity of the rt-RPA assay were 100% in practice compared to the reference methods.

CONCLUSION

The automatic comparison framework for molecular biomarker mining is straightforward, universal, applicable, and efficient. Based on recognizing the BCC-specific protein SecY and its gene, we successfully established the rt-RPA assay for rapid detection in pharmaceutical and personal care products.

摘要

目的

基于微生物蛋白质组和基因组数据比较的大数据分析,挖掘特定蛋白质及其蛋白质编码基因,作为复杂(BCC)细菌检测的合适分子生物标志物,并开发一种实时重组酶聚合酶扩增(rt-RPA)检测方法,用于快速等温筛选药品和个人护理产品。

方法

我们构建了一个基于Python的自动筛选框架,比较78株BCC菌株和263株非BCC菌株的微生物蛋白质组,以鉴定BCC特异性蛋白质序列。此外,使用包含15.8万种细菌的自建基因组数据库验证了特定蛋白质编码基因及其核心DNA序列。通过58株纯培养菌株和33批人工污染的药品和个人护理产品,评估了使用rt-RPA检测BCC的合适方法。

结果

我们通过自动比较框架鉴定出蛋白质SecY及其蛋白质编码基因。对该基因保守区域的虚拟评估显示,来自基因组数据库的特异性超过99.8%,通过系统发育分析可以将所有已知的BCC物种与其他细菌区分开来。此外,针对该基因的rt-RPA检测在纯培养物中对BCC细菌的检测限为5.6×10 CFU,或在30分钟内对1.2 pg BCC细菌基因组DNA的检测限为1.2 pg。经过预富集过程后,经验证可从人工污染样品中检测出<1 CFU/份的BCC细菌。与参考方法相比,rt-RPA检测在实际应用中的相对真实性和灵敏度均为100%。

结论

用于分子生物标志物挖掘的自动比较框架简单、通用、适用且高效。基于识别BCC特异性蛋白质SecY及其基因,我们成功建立了用于药品和个人护理产品快速检测的rt-RPA检测方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e15/10539473/486ae5d15ba0/fmicb-14-1270760-g001.jpg

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