| Title: | Digital PCR-based genotyping: a precision approach to HCMV drug resistance |
|---|
| Authors: | ID Milavec, Mojca (Author)
ID Cvelbar, Tašja (Author)
ID Bogožalec Košir, Alexandra (Author) |
|---|
| Files: |  URL - Source URL, visit https://link.springer.com/protocol/10.1007/978-1-0716-4642-7_2
 PDF - Presentation file. (916,86 KB, This file will be accessible after 29.06.2026)
MD5: F5454C140FC4A16C98C3EF95FDB7518F
|
|---|
| Language: | English |
|---|
| Typology: | 1.16 - Independent Scientific Component Part or a Chapter in a Monograph |
|---|
| Organization: |  NIB - National Institute of Biology
|
|---|
| Abstract: | 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. |
|---|
| Keywords: | digital PCR, human cytomegalovirus, antimicrobial drug resistance, mutations |
|---|
| Publication status: | Published |
|---|
| Publication version: | Author Accepted Manuscript |
|---|
| Publication date: | 29.06.2025 |
|---|
| Year of publishing: | 2025 |
|---|
| Number of pages: | Str. 19-29 |
|---|
| PID: | 20.500.12556/DiRROS-23689  |
|---|
| UDC: | 577.2 |
|---|
| DOI: | 10.1007/978-1-0716-4642-7_2 |
|---|
| COBISS.SI-ID: | 246361091 |
|---|
| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 22. 8. 2025;
|
|---|
| Publication date in DiRROS: | 25.09.2025 |
|---|
| Views: | 237 |
|---|
| Downloads: | 40 |
|---|
| Metadata: |    |
|---|
|
:
|
Copy citation |
|---|
| | | | Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
