Журнал микробиологии, эпидемиологии и иммунобиологии. 2021; 98: 697-705
Определение чувствительности Mycobacterium tuberculosis к противотуберкулёзным препаратам с помощью полногеномного секвенирования и программного обеспечения «Mykrobe»
https://doi.org/10.36233/0372-9311-191Аннотация
Введение. Чувствительность Mycobacterium tuberculosis к противотуберкулёзным препаратам устанавливается с помощью фенотипических и молекулярных методов. Анализ целого генома штаммов M. tuberculosis даёт возможность предсказывать резистентность к лекарствам для большого числа медикаментов. Для этого разработано несколько видов программного обеспечения.
Цель работы - определить чувствительность M. tuberculosis к антитуберкулёзным препаратам с помощью фенотипического и генотипического анализа, а также полногеномного секвенирования с использованием программного обеспечения «Mykrobe».
Материалы и методы. Исследовали 34 мультирезистентных штамма M. tuberculosis, выделенных из клинических материалов 34 пациентов в Болгарии. Все они были подтверждены фенотипически с помощью «BACTEC MGIT 960 System». Для определения резистентности к противотуберкулёзным средствам первого и второго ряда пользовались тестами для линейной гибридизации «Geno Type MTBDR plus v.1.0» и «Geno Type MTBDR sl v.1.0». Штаммы M. tuberculosis секвенировали с помощью «MiSeq». Для электронной резистограммы применяли программное обеспечение «Mykrobe v.0.8.1».
Результаты. Все три метода — фенотипический анализ, генетический анализ и электронная резистограмма с помощью программного обеспечения «Mykrobe» — дали сопоставимые результаты чувствительности/резистентности исследуемых штаммов. Все фенотипически доказанные штаммы, резистентные к рифампицину и изониазиду, были подтверждены на 100% с помощью программного обеспечения «Mykrobe». Мутация С-15Т является маркером для резистентности к изониазиду у исследуемых нами штаммов со сполиготипом SIT41. Мы наблюдали 75% (21/28) совпадения результатов по «BACTEC» и «Mykrobe» в отношении резистентности к этамбутолу. Фенотипически 87% (n = 27) штаммов были устойчивы к стрептомицину, и лишь 59% (n = 19) доказаны программным обеспечением «Mykrobe» как таковые. Сравнивая фенотипическую и генотипическую резистентность к офлоксацину, амикацину и канамицину, мы наблюдали совпадение результатов на 100%.
Выводы. Секвенирование целого генома относительно дорого и трудоёмко, но представляет собой ценный инструмент эпидемиологического генотипирования и определения восприимчивости к лекарственным средствам.
Список литературы
1. WHO. European Centre for Disease Prevention and Control, WHO Regional Office for Europe. Tuberculosis surveillance and monitoring in Europe 2021 – 2019 data. Copenhagen; 2021. Available at: https://www.ecdc.europa.eu/en/publications-data/tuberculosissurveillance-and-monitoring-europe-2021-2019-data
2. Jagielski T. Partnership to Fight Against TB in Central and Eastern Europe (FATE). FATE: the new partnership to Fight Against TB in Central and Eastern Europe. Lancet Infect. Dis. 2017; 17(4): 363. https://doi.org/10.1016/S1473-3099(17)30120-2
3. Milanov V., Falzon D., Zamfirova M., Varleva T., Bachiyska E., Koleva A., et al. Factors associated with treatment success and death in cases with multidrug-resistant tuberculosis in Bulgaria, 2009–2010. Int. J. Mycobacteriol. 2015; 4(2): 131–7. https://doi.org/10.1016/j.ijmyco.2015.03.005
4. Yordanova S., Baykova A., Atanasova Y., Todorova Y., Bachiyska E. Isoniazid-monoresistant tuberculosis in Bulgaria. Probl. Inf. Parasit. Dis. 2020; 48(1): 21–4. Available at: https://pipd.ncipd.org/index.php/pipd/article/view/29
5. Singh A., Prasad R., Balasubramanian V., Gupta N. Drug-resistant tuberculosis and HIV infection: current perspectives. HIV AIDS (Auckl.). 2020; 12: 9–31. https://doi.org/10.2147/HIV.S193059
6. van der Werf M.J., Ködmön C., Zucs P., Hollo V., Amato-Gauci A.J., Pharris A. Tuberculosis and HIV coinfection in Europe: looking at one reality from two angles. AIDS. 2016; 30(18): 2845–53. https://doi.org/10.1097/QAD.0000000000001252
7. Yancheva-Petrova N.A., Milanov V., Strashimirov D., Kostadinov D. Case of an HIV-positive patient co-infected with multidrug-resistant tuberculosis. Probl. Inf. Parasit. Dis. 2019; 47(1): 21. Available at: https://pipd.ncipd.org/index.php/pipd/article/view/47_1_4_CASE_OF_AN_HIV-_POSITIVE_PATIENT_CO-INFECTED_WITH_MULTIDR
8. Miotto P., Tessema B., Tagliani E., Chindelevitch L., Starks A.M., Emerson C., et al. A standardized method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis. Eur. Respir. J. 2017; 50(6): 1701354. https://doi.org/10.1183/13993003.01354-2017
9. Satta G., Atzeni A., McHugh T.D. Mycobacterium tuberculosis and whole genome sequencing: a practical guide and online tools available for the clinical microbiologist. Clin. Microbiol. Infect. 2017; 23(2): 69–72. https://doi.org/10.1016/j.cmi.2016.09.005
10. Papaventsis D., Casali N., Kontsevaya I., Drobniewski F., Cirillo D.M., Nikolayevskyy V. Whole genome sequencing of Mycobacterium tuberculosis for detection of drug resistance: a systematic review. Clin. Microbiol. Infect. 2017; 23(2): 61–8. https://doi.org/10.1016/j.cmi.2016.09.008
11. Tagliani E., Anthony R., Kohl T.A., de Neeling A., Nikolayevskyy V., Ködmön C., et al. Use of a whole genome sequencing- based approach for Mycobacterium tuberculosis surveillance in Europe in 2017–2019: An ECDC pilot study. Eur. Respir. J. 2020; 57(1): 2002272. https://doi.org/10.1183/13993003.02272-2020
12. Hunt M., Mather A.E., Sánchez-Busó L., Page A.J., Parkhill J., Keane J.A., et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb. Genom. 2017; 3(10): e000131. https://doi.org/10.1099/mgen.0.000131
13. Yang Y., Jiang X., Chai B., Ma L., Li B., Zhang A., et al. ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database. Bioinformatics. 2016; 32(15): 2346–51. https://doi.org/10.1093/bioinformatics/btw136
14. Gupta S.K., Padmanabhan B.R., Diene S.M., Lopez-Rojas R., Kempf M., Landraud L., et al. ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob. Agents Chemother. 2014; 58(1): 212–20. https://doi.org/10.1128/AAC.01310-13
15. Iwai H., Kato-Miyazawa M., Kirikae T., Miyoshi-Akiyama T. CASTB (the comprehensive analysis server for the Mycobacterium tuberculosis complex): A publicly accessible web server for epidemiological analyses, drug-resistance prediction and phylogenetic comparison of clinical isolates. Tuberculosis (Edinb.). 2015; 95(6): 843–4. https://doi.org/10.1016/j.tube.2015.09.002
16. Steiner A., Stucki D., Coscolla M., Borrell S., Gagneux S. KvarQ: targeted and direct variant calling from fastq reads of bacterial genomes. BMC Genomics. 2014; 15(1): 881. https://doi.org/10.1186/1471-2164-15-881
17. Kohl T.A., Utpatel C., Schleusener V., De Filippo M.R., Beckert P., Cirillo D.M., et al. MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates. PeerJ. 2018; 6: e5895. https://doi.org/10.7717/peerj.5895
18. Feuerriegel S., Schleusener V., Beckert P., Kohl T.A., Miotto P., Cirillo D.M., et al. PhyResSE: a web tool delineating Mycobacterium tuberculosis antibiotic resistance and lineage from whole-genome sequencing data. J. Clin. Microbiol. 2015; 53(6): 1908–14. https://doi.org/10.1128/JCM.00025-15
19. Davis J.J., Boisvert S., Brettin T., Kenyon R.W., Mao C., Olson R., et al. Antimicrobial resistance prediction in PATRIC and RAST. Sci. Rep. 2016; 6(1): 27930. https://doi.org/10.1038/srep27930
20. Zankari E., Hasman H., Cosentino S., Vestergaard M., Rasmussen S., Lund O., et al. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 2012; 67(11): 2640–4. https://doi.org/10.1093/jac/dks261
21. McArthur A.G., Waglechner N., Nizam F., Yan A., Azad M.A., Baylay A.J., et al. The comprehensive antibiotic resistance database. Antimicrob. Agents Chemother. 2013; 57(7): 3348–57. https://doi.org/10.1128/AAC.00419-13
22. Inouye M., Dashnow H., Raven L.A., Schultz M.B., Pope B.J., Tomita T., et al. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Med. 2014; 6(11): 90. https://doi.org/10.1186/s13073-014-0090-6
23. de Man T.J., Limbago B.M. SSTAR, a stand-alone easy-to-use antimicrobial resistance gene predictor. mSphere. 2016; 1(1): e00050-15. https://doi.org/10.1128/mSphere.00050-15
24. Phelan J.E., Lim D.R., Mitarai S., de Sessions P.F., Tujan M.A.A., Reyes L.T., et al. Mycobacterium tuberculosis whole genome sequencing provides insights into the Manila strain and drug-resistance mutations in the Philippines. Sci. Rep. 2019; 9(1): 9305. https://doi.org/10.1038/s41598-019-45566-5
25. Coll F., McNerney R., Preston M.D., Guerra-Assunção J.A., Warry A., Hill-Cawthorne G., et al. Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences. Genome Med. 2015; 7(1): 51. https://doi.org/10.1186/s13073-015-0164-0
26. Hunt M., Bradley P., Lapierre S.G., Heys S., Thomsit M., Hall M.B., et al. Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe. Wellcome Open Res. 2019; 4: 191. https://doi.org/10.12688/wellcomeopenres.15603.1
27. van Soolingen D., de Haas P.E., Hermans P.W., van Embden J.D. DNA fingerprinting of Mycobacterium tuberculosis. Methods Enzymol. 1994; 235: 196–205. https://doi.org/10.1016/0076-6879(94)35141-4
28. Bradley P., Gordon N., Walker T., Dunn L., Heys S., Huang B., et al. Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nat. Commun. 2015; 6: 10063. https://doi.org/10.1038/ncomms10063
29. Panaiotov S., Hodzhev Y., Tolchkov V., Tsafarova B., Mihailov A., Stefanova T. Complete genome sequence, genome stability and phylogeny of the vaccine strain Mycobacterium bovis BCG SL222 Sofia. Vaccines (Basel). 2021; 9(3): 237. https://doi.org/10.3390/vaccines9030237
30. Bachiyska E., Yordanova S., Atanasova Y. Phenotypic and genetic characterization of tuberculosis strains in Bulgaria in 2011. InSpiro. 2013; (1): 38–41. (in Bulgarian)
31. Panaiotov S., Bachiyska E., Yordanova S. Genetic biodiversity of sensitive and multi-resistant strains of Mycobacterium tuberculosis in Bulgaria. Med. Rev. 2016; 52(3): 47–54. (in Bulgarian)
32. Yordanova S., Bachiyska E., Atanasova Y. Multidrug resistant tuberculosis in Bulgaria — microbiological aspects. Probl. Inf. Parasit. Dis. 2013; 41: 5–8.
33. Bachiyska E., Yordanova S., Atanasova Y. Multi drug resistant tuberculosis in Bulgaria — gene mutations associated. InSpiro. 2016; 37: 36–40. (in Bulgarian)
34. Yordanova S., Bachiyska E., Atanasova Y. MDR-TB with additional fluoroquinolone resistance in Bulgaria. Probl. Inf. Paras. Dis. 2015; 43(2): 8–11.
35. Kohl T.A., Utpatel C., Schleusener V., De Filippo M.R., Beckert P., Cirillo D.M., et al. MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates. PeerJ. 2018; 6: e5895. https://doi.org/10.7717/peerj.5895
Journal of microbiology, epidemiology and immunobiology. 2021; 98: 697-705
Drug susceptibility testing of Mycobacterium tuberculosis using next generation sequencing and Mykrobe software
https://doi.org/10.36233/0372-9311-191Abstract
Introduction. Mycobacterium tuberculosis is the causative agent of tuberculosis. Drug susceptibility testing is performed by phenotypic and molecular tests. Commonly used for phenotypic drug susceptibility testing is the automated BACTEC system in a liquid culture medium. Drug susceptibility by line probe molecular tests was introduced almost 15 years ago. Recently whole genome sequencing (WGS) analysis of M. tuberculosis strains demonstrated that genotyping of drug-resistance could be accurately performed. Several software tools were developed.
Our study aimed to perform whole-genome sequencing on phenotypically confirmed multi-drug resistant (MDR) M. tuberculosis strains, to identify drug-resistant mutations and to compare whole-genome sequencing profiles with line probe assay and phenotypic results.
Materials and methods. We performed analysis on 34 MDR M. tuberculosis Bulgarian strains. Phenotypic drug susceptibility testing was performed on the BACTEC system. For molecular testing of drug susceptibility to first- and second-line tuberculostatics, we applied line probe assay Geno Type MTBDR plus v.1.0 и Geno Type MTBDR sl v.1.0. Sequencing was performed on MiSeq. Generated FASTQ files were analyzed for known drugresistant mutations with the software platform Mykrobe v.0.8.1.
Results. All three methods — phenotypic analysis using the BACTEC system, genetic analysis of strains applying the Geno Type test and Mykrobe software gave comparable sensitivity/resistance results for the studied strains. All phenotypically proven rifampicin and isoniazid-resistant strains were 100% confirmed using Mykrobe software. The C-15T mutation is a marker for isoniazid resistance in strains of the SIT41 spoligotype. We observed a 75% (21/28) agreement between BACTEC and Mykrobe for ethambutol resistance. Phenotypically, 87% (n = 27) of the strains are resistant to streptomycin, but only 59% (n = 19) are proven by Mykrobe software. Comparing phenotypic and genotypic resistance to ofloxacin, amikacin and kanamycin, we observed 100% coincidence of results.
Conclusions. Whole-genome sequencing approach is relatively expensive and laborious but useful for detailed analysis such as epidemiological genotyping and molecular drug susceptibility testing.
References
1. WHO. European Centre for Disease Prevention and Control, WHO Regional Office for Europe. Tuberculosis surveillance and monitoring in Europe 2021 – 2019 data. Copenhagen; 2021. Available at: https://www.ecdc.europa.eu/en/publications-data/tuberculosissurveillance-and-monitoring-europe-2021-2019-data
2. Jagielski T. Partnership to Fight Against TB in Central and Eastern Europe (FATE). FATE: the new partnership to Fight Against TB in Central and Eastern Europe. Lancet Infect. Dis. 2017; 17(4): 363. https://doi.org/10.1016/S1473-3099(17)30120-2
3. Milanov V., Falzon D., Zamfirova M., Varleva T., Bachiyska E., Koleva A., et al. Factors associated with treatment success and death in cases with multidrug-resistant tuberculosis in Bulgaria, 2009–2010. Int. J. Mycobacteriol. 2015; 4(2): 131–7. https://doi.org/10.1016/j.ijmyco.2015.03.005
4. Yordanova S., Baykova A., Atanasova Y., Todorova Y., Bachiyska E. Isoniazid-monoresistant tuberculosis in Bulgaria. Probl. Inf. Parasit. Dis. 2020; 48(1): 21–4. Available at: https://pipd.ncipd.org/index.php/pipd/article/view/29
5. Singh A., Prasad R., Balasubramanian V., Gupta N. Drug-resistant tuberculosis and HIV infection: current perspectives. HIV AIDS (Auckl.). 2020; 12: 9–31. https://doi.org/10.2147/HIV.S193059
6. van der Werf M.J., Ködmön C., Zucs P., Hollo V., Amato-Gauci A.J., Pharris A. Tuberculosis and HIV coinfection in Europe: looking at one reality from two angles. AIDS. 2016; 30(18): 2845–53. https://doi.org/10.1097/QAD.0000000000001252
7. Yancheva-Petrova N.A., Milanov V., Strashimirov D., Kostadinov D. Case of an HIV-positive patient co-infected with multidrug-resistant tuberculosis. Probl. Inf. Parasit. Dis. 2019; 47(1): 21. Available at: https://pipd.ncipd.org/index.php/pipd/article/view/47_1_4_CASE_OF_AN_HIV-_POSITIVE_PATIENT_CO-INFECTED_WITH_MULTIDR
8. Miotto P., Tessema B., Tagliani E., Chindelevitch L., Starks A.M., Emerson C., et al. A standardized method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis. Eur. Respir. J. 2017; 50(6): 1701354. https://doi.org/10.1183/13993003.01354-2017
9. Satta G., Atzeni A., McHugh T.D. Mycobacterium tuberculosis and whole genome sequencing: a practical guide and online tools available for the clinical microbiologist. Clin. Microbiol. Infect. 2017; 23(2): 69–72. https://doi.org/10.1016/j.cmi.2016.09.005
10. Papaventsis D., Casali N., Kontsevaya I., Drobniewski F., Cirillo D.M., Nikolayevskyy V. Whole genome sequencing of Mycobacterium tuberculosis for detection of drug resistance: a systematic review. Clin. Microbiol. Infect. 2017; 23(2): 61–8. https://doi.org/10.1016/j.cmi.2016.09.008
11. Tagliani E., Anthony R., Kohl T.A., de Neeling A., Nikolayevskyy V., Ködmön C., et al. Use of a whole genome sequencing- based approach for Mycobacterium tuberculosis surveillance in Europe in 2017–2019: An ECDC pilot study. Eur. Respir. J. 2020; 57(1): 2002272. https://doi.org/10.1183/13993003.02272-2020
12. Hunt M., Mather A.E., Sánchez-Busó L., Page A.J., Parkhill J., Keane J.A., et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb. Genom. 2017; 3(10): e000131. https://doi.org/10.1099/mgen.0.000131
13. Yang Y., Jiang X., Chai B., Ma L., Li B., Zhang A., et al. ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database. Bioinformatics. 2016; 32(15): 2346–51. https://doi.org/10.1093/bioinformatics/btw136
14. Gupta S.K., Padmanabhan B.R., Diene S.M., Lopez-Rojas R., Kempf M., Landraud L., et al. ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob. Agents Chemother. 2014; 58(1): 212–20. https://doi.org/10.1128/AAC.01310-13
15. Iwai H., Kato-Miyazawa M., Kirikae T., Miyoshi-Akiyama T. CASTB (the comprehensive analysis server for the Mycobacterium tuberculosis complex): A publicly accessible web server for epidemiological analyses, drug-resistance prediction and phylogenetic comparison of clinical isolates. Tuberculosis (Edinb.). 2015; 95(6): 843–4. https://doi.org/10.1016/j.tube.2015.09.002
16. Steiner A., Stucki D., Coscolla M., Borrell S., Gagneux S. KvarQ: targeted and direct variant calling from fastq reads of bacterial genomes. BMC Genomics. 2014; 15(1): 881. https://doi.org/10.1186/1471-2164-15-881
17. Kohl T.A., Utpatel C., Schleusener V., De Filippo M.R., Beckert P., Cirillo D.M., et al. MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates. PeerJ. 2018; 6: e5895. https://doi.org/10.7717/peerj.5895
18. Feuerriegel S., Schleusener V., Beckert P., Kohl T.A., Miotto P., Cirillo D.M., et al. PhyResSE: a web tool delineating Mycobacterium tuberculosis antibiotic resistance and lineage from whole-genome sequencing data. J. Clin. Microbiol. 2015; 53(6): 1908–14. https://doi.org/10.1128/JCM.00025-15
19. Davis J.J., Boisvert S., Brettin T., Kenyon R.W., Mao C., Olson R., et al. Antimicrobial resistance prediction in PATRIC and RAST. Sci. Rep. 2016; 6(1): 27930. https://doi.org/10.1038/srep27930
20. Zankari E., Hasman H., Cosentino S., Vestergaard M., Rasmussen S., Lund O., et al. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 2012; 67(11): 2640–4. https://doi.org/10.1093/jac/dks261
21. McArthur A.G., Waglechner N., Nizam F., Yan A., Azad M.A., Baylay A.J., et al. The comprehensive antibiotic resistance database. Antimicrob. Agents Chemother. 2013; 57(7): 3348–57. https://doi.org/10.1128/AAC.00419-13
22. Inouye M., Dashnow H., Raven L.A., Schultz M.B., Pope B.J., Tomita T., et al. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Med. 2014; 6(11): 90. https://doi.org/10.1186/s13073-014-0090-6
23. de Man T.J., Limbago B.M. SSTAR, a stand-alone easy-to-use antimicrobial resistance gene predictor. mSphere. 2016; 1(1): e00050-15. https://doi.org/10.1128/mSphere.00050-15
24. Phelan J.E., Lim D.R., Mitarai S., de Sessions P.F., Tujan M.A.A., Reyes L.T., et al. Mycobacterium tuberculosis whole genome sequencing provides insights into the Manila strain and drug-resistance mutations in the Philippines. Sci. Rep. 2019; 9(1): 9305. https://doi.org/10.1038/s41598-019-45566-5
25. Coll F., McNerney R., Preston M.D., Guerra-Assunção J.A., Warry A., Hill-Cawthorne G., et al. Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences. Genome Med. 2015; 7(1): 51. https://doi.org/10.1186/s13073-015-0164-0
26. Hunt M., Bradley P., Lapierre S.G., Heys S., Thomsit M., Hall M.B., et al. Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe. Wellcome Open Res. 2019; 4: 191. https://doi.org/10.12688/wellcomeopenres.15603.1
27. van Soolingen D., de Haas P.E., Hermans P.W., van Embden J.D. DNA fingerprinting of Mycobacterium tuberculosis. Methods Enzymol. 1994; 235: 196–205. https://doi.org/10.1016/0076-6879(94)35141-4
28. Bradley P., Gordon N., Walker T., Dunn L., Heys S., Huang B., et al. Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nat. Commun. 2015; 6: 10063. https://doi.org/10.1038/ncomms10063
29. Panaiotov S., Hodzhev Y., Tolchkov V., Tsafarova B., Mihailov A., Stefanova T. Complete genome sequence, genome stability and phylogeny of the vaccine strain Mycobacterium bovis BCG SL222 Sofia. Vaccines (Basel). 2021; 9(3): 237. https://doi.org/10.3390/vaccines9030237
30. Bachiyska E., Yordanova S., Atanasova Y. Phenotypic and genetic characterization of tuberculosis strains in Bulgaria in 2011. InSpiro. 2013; (1): 38–41. (in Bulgarian)
31. Panaiotov S., Bachiyska E., Yordanova S. Genetic biodiversity of sensitive and multi-resistant strains of Mycobacterium tuberculosis in Bulgaria. Med. Rev. 2016; 52(3): 47–54. (in Bulgarian)
32. Yordanova S., Bachiyska E., Atanasova Y. Multidrug resistant tuberculosis in Bulgaria — microbiological aspects. Probl. Inf. Parasit. Dis. 2013; 41: 5–8.
33. Bachiyska E., Yordanova S., Atanasova Y. Multi drug resistant tuberculosis in Bulgaria — gene mutations associated. InSpiro. 2016; 37: 36–40. (in Bulgarian)
34. Yordanova S., Bachiyska E., Atanasova Y. MDR-TB with additional fluoroquinolone resistance in Bulgaria. Probl. Inf. Paras. Dis. 2015; 43(2): 8–11.
35. Kohl T.A., Utpatel C., Schleusener V., De Filippo M.R., Beckert P., Cirillo D.M., et al. MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates. PeerJ. 2018; 6: e5895. https://doi.org/10.7717/peerj.5895
