Milavec Mojca, Cvelbar Tašja, Bogožalec Košir Alexandra
Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia.
Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
Methods Mol Biol. 2025;2943:19-29. doi: 10.1007/978-1-0716-4642-7_2.
The genotyping workflow described uses digital PCR (dPCR) to detect and quantify drug resistance mutations in human cytomegalovirus (HCMV). The method focuses on the detection and quantification of three common mutations in the UL97 gene at codons 460, 594, and 595, which are responsible for the majority of ganciclovir-resistant clinical isolates. The dPCR approach offers high sensitivity and accuracy, making it suitable for routine testing as well as a reference measurement procedure for external quality assessment schemes. The workflow includes several key steps: DNA isolation, preparation of the dPCR reaction mixture, partitioning, thermocycling, and data analysis. This method improves the detection capabilities of HCMV drug resistance and provides a robust and efficient tool for clinical and research applications.
所述基因分型工作流程采用数字PCR（dPCR）来检测和定量人类巨细胞病毒（HCMV）中的耐药性突变。该方法着重于检测和定量UL97基因中第460、594和595位密码子的三种常见突变，这些突变是大多数耐更昔洛韦临床分离株的原因。dPCR方法具有高灵敏度和准确性，适用于常规检测以及外部质量评估计划的参考测量程序。该工作流程包括几个关键步骤：DNA分离、dPCR反应混合物的制备、分区、热循环和数据分析。该方法提高了HCMV耐药性的检测能力，并为临床和研究应用提供了一个强大而有效的工具。
