| Title: | Development of novel digital PCR assays for the rapid quantification of Gram-negative bacteria biomarkers using RUCS algorithm |
|---|
| Authors: | ID Bogožalec Košir, Alexandra (Author)
ID Alič, Špela (Author)
ID Tomič, Viktorija (Author)
ID Lužnik, Dane (Author)
ID Dreo, Tanja (Author)
ID Milavec, Mojca (Author) |
|---|
| Files: |  URL - Source URL, visit https://doi.org/10.1016/j.ymeth.2024.10.011
|
|---|
| Language: | English |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: |  NIB - National Institute of Biology
|
|---|
| Abstract: | Rapid and accurate identification of bacterial pathogens is crucial for effective treatment and infection control, particularly in hospital settings. Conventional methods like culture techniques and MALDI-TOF mass spectrometry are often time-consuming and less sensitive. This study addresses the need for faster and more precise diagnostic methods by developing novel digital PCR (dPCR) assays for the rapid quantification of biomarkers from three Gram-negative bacteria: Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Utilizing publicly available genomes and the rapid identification of PCR primers for unique core sequences or RUCS algorithm, we designed highly specific dPCR assays. These assays were validated using synthetic DNA, bacterial genomic DNA, and DNA extracted from clinical samples. The developed dPCR methods demonstrated wide linearity, a low limit of detection (approx. 30 copies per reaction), and robust analytical performance with measurement uncertainty below 25 %. The assays showed high repeatability and intermediate precision, with no cross-reactivity observed. Comparison with MALDI-TOF mass spectrometry revealed substantial concordance, highlighting the methods’ suitability for clinical diagnostics. This study underscores the potential of dPCR for rapid and precise quantification of Gram-negative bacterial biomarkers. The developed methods offer significant improvements over existing techniques, providing faster, more accurate, and SI-traceable measurements. These advancements could enhance clinical diagnostics and infection control practices. |
|---|
| Keywords: | digital PCR (dPCR), Gram-negative bacteria, pathogen detection, respiratory infections, biomarkers, RUCS algorithm |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Publication date: | 01.12.2024 |
|---|
| Year of publishing: | 2024 |
|---|
| Number of pages: | str. 72-80 |
|---|
| Numbering: | Vol. 232 |
|---|
| UDC: | 579 |
|---|
| ISSN on article: | 1046-2023 |
|---|
| DOI: | 10.1016/j.ymeth.2024.10.011  |
|---|
| COBISS.SI-ID: | 213682691 |
|---|
| Note: | Soavtorji: Špela Alič, Viktorija Tomič, Dane Lužnik, Tanja Dreo, Mojca Milavec;
|
|---|
| Publication date in DiRROS: | 05.11.2024 |
|---|
| Views: | 14 |
|---|
| Downloads: | 5 |
|---|
| 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. |
