| Title: | Next-generation sequencing of drug resistant Mycobacterium tuberculosis clinical isolates in low-incidence countries |
|---|
| Authors: | ID Sodja, Eva, Klinika Golnik (Author)
ID Toplak, Nataša (Author)
ID Koren, Simon (Author)
ID Kovač, Minka (Author)
ID Truden, Sara, Klinika Golnik (Author)
ID Ilievska Poposka, Biljana (Author)
ID Žolnir-Dovč, Marija, Klinika Golnik (Author) |
|---|
| Files: |  PDF - Presentation file, download (144,02 KB)
MD5: C2CFCA57A3FFF065BB70F7D7CFD360E8
 URL - Source URL, visit https://www.iimmun.ru/iimm/article/view/851/883
|
|---|
| Language: | English |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: |  UKPBAG - University Clinic of Respiratory and Allergic Diseases Golnik
|
|---|
| Abstract: | Drug resistant tuberculosis (TB), especially multidrug (MDR) and extensively drug-resistant (XDR) TB, is still a serious problem in global TB control. Slovenia and North Macedonia are low-incidence countries with TB incidence rates of 5.4 and 10.4 in 2017, respectively. In both countries, the percentage of drug resistant TB is very low with sporadic cases of MDR-TB. However, global burden of drug-resistant TB continues to increase imposing huge impact on public health systems and strongly stimulating the detection of gene variants related with drug resistance in TB. Next-generation sequencing (NGS) can provide comprehensive analysis of gene variants linked to drug resistance in Mycobacterium tuberculosis. Therefore, the aim of our study was to examine the feasibility of a full-length gene analysis for the drug resistance related genes (inhA, katG, rpoB, embB) using Ion Torrent technology and to compare the NGS results with those obtained from conventional phenotypic drug susceptibility testing (DST) in TB isolates. Between 1996 and 2017, we retrospectively selected 56 TB strains from our National mycobacterial culture collection. Of those, 33 TB isolates from Slovenian patients were isolated from various clinical samples and subjected to phenotypic DST testing in Laboratory for Mycobacteria (University Clinic Golnik, Slovenia). The remaining 23 TB isolates were isolated from Macedonian patients and sent to our laboratory for assistance in phenotypic DST testing. TB strains included were either mono-, poly- or multidrug resistant. For control purposes, we also randomly selected five TB strains susceptible to first-line anti-TB drugs. High concordance between genetic (Ion Torrent technology) and standard phenotypic DST testing for isoniazid, rifampicin and ethambutol was observed, with percent of agreement of 77%, 93.4% and 93.3%, sensitivities of 68.2%, 100% and 100%, and specificities of 100%, 80% and 88.2%, respectively. In conclusion, the genotypic DST using Ion Torrent semiconductor NGS successfully predicted drug resistance with significant shortening of time needed to obtain the resistance profiles from several weeks to just a few days. |
|---|
| Keywords: | drug resistant tuberculosis, next-generation sequencing, low-incidence countries, phenotypic drug susceptibility testing |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Place of publishing: | Rusija |
|---|
| Publisher: | Saint-Petersburg Pasteur Institute |
|---|
| Year of publishing: | 2019 |
|---|
| Number of pages: | str. 773-778 |
|---|
| Numbering: | Vol. 9, no. 5/6 |
|---|
| PID: | 20.500.12556/DiRROS-12195  |
|---|
| UDC: | 616-002 |
|---|
| ISSN on article: | 2313-7398 |
|---|
| DOI: | 10.15789/2220-7619-2019-5-6-773-778 |
|---|
| COBISS.SI-ID: | 13128195 |
|---|
| Copyright: | Sodja E. et al., 2019 |
|---|
| Note: | Nasl. z nasl. zaslona;
Soavtorji iz Slovenije: N. Toplak, S. Koren, M. Kovač, S. Truden, M. Žolnir-Dovč;
Opis vira z dne 29. 4. 2020;
|
|---|
| Publication date in DiRROS: | 24.07.2020 |
|---|
| Views: | 2344 |
|---|
| Downloads: | 1269 |
|---|
| 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. |
