The proposed project aims to improve the control of tuberculosis and study its transmission routes, with a particular focus on the occurrence of MDR-TB outbreaks, using genomic epidemiology techniques, multi-omics analysis, and data mining using a new bioinformatics platform. Genome-wide analysis of local M. tuberculosis isolates will be performed, focusing primarily on the L2 family. Data analysis will identify phylogenetic and drug resistance-associated SNPs, deletion and insertion regions, and CRISPR structure. The bioinformatics platform will allow us to accurately identify clusters and classify subclades of the L2 lineage. In addition, genomic drug susceptibility testing (DST) will be compared with phenotypic DST; and the results of in silico spoligotyping will be confirmed by mass spectrometry. The proposed project aims to improve the control of tuberculosis and study its transmission routes with a special focus on the occurrence of MDR-TB outbreaks using methods of genomic epidemiology, multi-omics analysis, and data analysis using a new bioinformatics platform . Genome-wide analysis of local M. tuberculosis isolates will be performed, focusing primarily on the L2 family. Data analysis will identify phylogenetic and drug resistance-associated SNPs, deletion and insertion regions, and CRISPR structure. The bioinformatics platform will allow us to accurately identify clusters and classify subclades of the L2 lineage. In addition, genomic drug susceptibility testing (DST) will be compared with phenotypic DST; and the results of in silico spoligotyping will be confirmed by mass spectrometry.

Novelty

Tuberculosis (TB) caused by the Mycobacterium tuberculosis complex (MTBC) is a public health concern globally. According to the recent WHO report, approximately 6.4 million cases of TB and 1.6 million deaths were registered in 2021 versus 5.8 million cases of TB and 1.5 million deaths in 2020 worldwide. The burden of drug-resistant TB (DR-TB) is also estimated to have increased worldwide between 2020 and 2021 mainly due to COVID-19. The global COVID-19 pandemic has stressed the importance of integrated research for outbreak control including genomics, big data, and modeling. The tuberculosis pandemic, like COVID-19, is made up of many lineages that are evolving at different paces and are superimposed. In this sense, understanding the evolution of outbreaks is important for their control and the use of adequate public health measures. Whole-genome sequencing has been extremely useful in understanding transmission patterns, the development of drug resistance, and bacterial evolution. This research project is aimed to improve TB control and risks by studying tuberculosis transmission with a specific focus on the emergence of MDR-TB outbreaks by using genomic epidemiology and the demographic history of the TB disease in Kazakhstan and Central Asia. In this regard, WGS of local Mtb isolates will be carried out with emphasis on lineage 2.

Aim

We aimed to improve TB control by studying tuberculosis transmission with a specific focus on the emergence of MDR-TB outbreaks by using genomic epidemiology, data mining, and the demographic history of tuberculosis in Kazakhstan and Central Asia.

Expected results

1. Representative sample of Mycobacterium tuberculosis clinical isolates circulating in all regions of the Republic of Kazakhstan will be formed;

2. L2 isolates will be genotyped with real-time PCR using genotype-specific markers to select L2 isolates for whole genome sequencing. Whole genome sequences of the local M. tuberculosis L2 isolates representing all regions of the Republic of Kazakhstan will be produced;

3. A genomic dataset of local M. tuberculosis lineage 2 clinical isolates will be analyzed with computational bioinformatic pipeline;

4. Phylogenetic analysis, cluster definition and classification of the L2 lineage will be carried out with computational genomic pipeline. A pairwise distance matrix will be calculated;

5. In silico predicted spoligotypes of the clinical M. tuberculosis isolates will be validated with masss-spectrometry;

6. A reference set of multi-omics data for M. tuberculosis lineage 2 MDR outbreak clinical isolates and compare transcriptomic and proteomic differences between the hypervirulent and low-virulent strains using RNA-sequencing and label-free quantitative LC-MS/MS approach will be created.

Project Manager

Pavel Tarlykov, PhD, Associate Professor

(http://www.scopus.com/authid/detail.url?authorId=35076539700)

Publications by the project leader and research team members related to the project topic

1. Resistant Mycobacterium tuberculosis Clinical Isolate, 3485_MTB, from Nur-Sultan, Kazakhstan // Microbiology Resource Announcements. ‒ 2020. ‒ Vol.9, №10. ‒ P.e00025-00020. DOI 10.1128/MRA.00025-20. SJR-0.413
2. Tarlykov P., Atavliyeva S., Alenova A. et al. Genomic analysis of Latin American-Mediterranean family of Mycobacterium tuberculosis clinical strains from Kazakhstan // Memorias do Instituto Oswaldo Cruz. ‒ 2020. ‒ Vol.115, In press. Q2, IF-2.070
3. B. Klotoe, S. Kacimi, E. Costa-Conceicão, H. Gomes, R. Barcellos, S. Panaiotov, D. Haj Slimene, N. Sikhayeva, S. Sengstake, A. Schuitema, M. Akhalaia, A. Alenova, E. Zholdybayeva, P. Tarlykov, R. Anthony, G. Refrégier, C. Sola Genomic characterization of MDR/XDR-TB in Kazakhstan by a combination of high-throughput methods predominantly shows the ongoing transmission of L2/Beijing 94–32 central Asian/Russian clusters // BMC Infectious Diseases. ‒ 2019. ‒ Vol.19, №1. ‒ P.553. DOI 10.1186/s12879-019-4201-2 Q3, IF-2.688.
4. Jurisic A., Robin C., Tarlykov P. et al. Topokaryotyping demonstrates single cell variability and stress dependent variations in nuclear envelope associated domains // Nucleic Acids Res. ‒ 2018. ‒ Vol.46, №22. ‒ P.e135. DOI 10.1093/nar/gky818 Q1 IF-11.501.
5. Tarlykov P.V., Raiymbek D.R., Alenova A.K., Abildaev T.S., Ramankulov E.M. Geno-typing of M. tuberculosis isolates with multiple drug resistance circulating in the Southern regions of Kazakhstan // Tuberculosis and Lung Diseases. ‒ 2015. ‒ Vol.9. ‒ P.41-46. https://www.tibl-journal.com/jour/article/view/795 SJR-0.218
6. Shevtsov A, Ramanculov E, Shevtsova E, Kairzhanova A, Tarlykov P, Filipenko M, Dymova M, Abisheva G, Jailbekova A, Kamalova D, Chsherbakov A, Tulegenov S, Akhmetova A, Sytnik I, Karibaev T, Mukanov K. Genetic diversity of Brucella abortus and Brucella melitensis in Kazakhstan using MLVA-16 // Infect Genet Evol. ‒ 2015. ‒ Vol. 34. ‒ P. 173-180. DOI 10.1016/j.meegid.2015.07.008 Q3 IF-2.773.
7. Shevtsova E, Shevtsov A, Mukanov K, Filipenko M, Kamalova D, Sytnik I, Syzdykov M, Kuznetsov A, Akhmetova A, Zharova M, Karibaev T, Tarlykov P, Ramanculov E. Epidemiology of Brucellosis and Genetic Diversity of Brucella abortus in Kazakhstan // Plos One. ‒ 2016. ‒ Vol. 11, № 12. ‒ P. e0167496. DOI 10.1371/journal.pone.0167496 Q2 IF-2.74.
8. Shoaib M, Kulyyassov A, Robin C, Winczura K, Tarlykov P, Despas E, Kannouche P, Ramanculov E, Lipinski M, Ogryzko V. PUB-NChIP—“in vivo biotinylation” approach to study chromatin in proximity to a protein of interest // Genome Research. ‒ 2013. ‒ Vol. 23, № 2. ‒ P. 331-340. DOI 10.1101/gr.134874.111 Q1, IF-9.944.
9. Maaty WS, Selvig K, Ryder S, Tarlykov P, Hilmer J, Heinemann J, Steffens J, Snyder J, Ortmann A, Douglas T, Young M, Bothner B. Proteomic Analysis of Sulfolobus solfataricus during Sulfolobus Turreted Icosahedral Virus Infection // J Proteome Res. ‒ 2012. ‒ Vol. 11, № 2. ‒ P. 1420-1432. DOI 10.1021/pr201087v Q1, IF-3.78
10. E.V. Zholdybayeva, Y.A. Talzhanov, A.M. Aitkulova, P.V. Tarlykov, G.N. Kulmambetova, A.N. Iskakova, A.U. Dzholdasbekova, O.A. Visternichan, D.Zh. Taizhanova, Y.M. Ramanculov Genetic risk factors for restenosis after percutaneous coronary intervention in Kazakh population // Human Genomics. ‒ 2016. ‒ Vol. 10, № 1. ‒ P. 1-8. 10.1186/s40246-