Jiang Shuai, Zhao Gaili, Ding Yunyun, Ye Shunxing, Li Zeqi, You Changqiao, Yin Yan, Guo Xinhong
College of Biology, Hunan University, Changsha, China.
College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, China.
Front Microbiol. 2024 Dec 23;15:1474406. doi: 10.3389/fmicb.2024.1474406. eCollection 2024.
Dengue viruses (DENVs), the causative agents of dengue hemorrhagic fever and dengue shock syndrome, undergo genetic mutations that result in new strains and lead to ongoing global re-infections.
To address the growing complexity of identifying and tracking biological samples, this study screened RNA barcode segments for the four DENV serotypes, ensuring high specificity and recall rates for DENV identification using segments.
Through analyzing complete genome sequences of DENVs, we screened eight barcode segments for DENV, DENV-1, DENV-2, DENV-3, and DENV-4 identification. Comparing the screened barcode segments to sequences of known strains and determining the proportion of correctly or incorrectly identified nucleotides, these segments demonstrated an average recall rate at nucleotide level of 91.34% for four DENV serotypes, a specificity of 99.50% at species level within the family, and a precision rate of 100% for identifying DENVs. For arboviruses, the nucleotide-level specificity was 63.58%. We designed and used the "Barcoding" software to streamline segment design, integrating automated sequence preprocessing, evaluation of barcode segments, and primer design, significantly reducing manual intervention and enhancing overall efficiency. We also established an online database called "Barcodes" for storing and preparing barcode segments.
This work established a standard framework for DENV identification and barcode segment selection, promising significant advancements in the real-time management and control of DENVs, thereby enhancing surveillance capabilities and facilitating targeted interventions in dengue outbreak-prone regions.
登革病毒（DENV）是登革出血热和登革休克综合征的病原体，会发生基因突变，产生新的毒株，导致全球范围内持续出现再感染情况。
为应对识别和追踪生物样本日益复杂的问题，本研究筛选了四种登革病毒血清型的RNA条形码片段，以确保使用这些片段进行登革病毒鉴定时具有高特异性和召回率。
通过分析登革病毒的全基因组序列，我们筛选出了八个用于鉴定登革病毒、登革-1型病毒、登革-2型病毒、登革-3型病毒和登革-4型病毒的条形码片段。将筛选出的条形码片段与已知毒株的序列进行比较，并确定正确或错误识别的核苷酸比例，这些片段在核苷酸水平上对四种登革病毒血清型的平均召回率为91.34%，在该科内物种水平上的特异性为99.50%，鉴定登革病毒的准确率为100%。对于虫媒病毒，核苷酸水平的特异性为63.58%。我们设计并使用了“条形码”软件来简化片段设计，集成了自动化序列预处理、条形码片段评估和引物设计，显著减少了人工干预并提高了整体效率。我们还建立了一个名为“条形码”的在线数据库，用于存储和准备条形码片段。
这项工作建立了登革病毒鉴定和条形码片段选择的标准框架，有望在登革病毒的实时管理和控制方面取得重大进展，从而提高监测能力，并便于在登革热高发地区进行有针对性的干预。
