Browsing by Author "Norvaiša, Inga"

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    Advantages of analysing both pairwise SNV-distance and differing SNVs between Mycobacterium tuberculosis isolates for recurrent tuberculosis cause determination.
    (2023-03-01) Sadovska, Darja; Nodieva, Anda; Pole, Ilva; Ķimsis, Jānis; Vīksna, Anda; Ozere, Iveta; Norvaiša, Inga; Bandere, Dace; Ranka, Renāte; Department of Infectology; Department of Pharmaceutical Chemistry
    Endogenous reactivation and exogenous reinfection are two possible causes of recurrent tuberculosis (TB). However, in some cases, precise cause determination can be challenging. In this study, we used whole genome sequencing to determine pairwise SNV distances and detect differing SNVs in initial and subsequent isolates for recurrent TB cases when the first and second episodes were caused by Mycobacterium tuberculosis ( Mtb) strains with an identical spoligotype pattern. In total, 104 Mtb isolates from 36 recurrent TB and 16 single TB episode patients were included in the study. Most isolate pairs belonged to the SIT1 (n=21), SIT42 (n=9), SIT53 (n=9), and SIT254 (n=7) spoligotypes, and in 27 cases, resistance to at least one anti-TB drug was found in either isolate. Drug susceptibility was more common in the recurrent TB patient cohort, and longitudinal single TB episode isolates were more prone to be drug-resistant (p=0.03), while the association between patient cohort and spoligotype was not statistically significant (p=0.07). The pairwise SNV-distance between the longitudinal single TB episode isolates was small (0-7 SNVs). Among the recurrent TB isolates, based on the high SNV-distance (38-273 SNVs), six reinfection cases (16.7%) were identified. This distance was small (<10 SNVs) in the remaining 30 isolate pairs. Further analysis of differing SNVs revealed that 22 (61.1%) cases could be classified as possible reactivation. Notably, despite the small distance of 2-7 SNVs, initial isolates of eight patients (22.2%) had several SNVs that were not found in the second isolates; therefore, these cases were classified as reinfection with a closely related Mtb strain. No statistically significant difference in the time interval between specimen collection in the reactivation and reinfection Mtb sample groups (p=0.13) or an association between recurrence cause and drug resistance status (p=0.62) or spoligotype (p=0.79) could be detected. The mycobacterial median mutation rate of longitudinal single TB episodes and possible reactivation isolate pairs (n=37) was 0.12 SNVs/genome/year (IQR 0-0.39), and in 18 cases (48.6%), it was equal to zero. No statistically significant differences in mutation rate were found between recurrent TB and longitudinal single TB episode isolates (p=0.087), drug-susceptible and resistant isolates (p=0.37) or isolates of Beijing and other genotype families (p=0.33). Furthermore, four cases of fluoroquinolone resistance development through the acquired SNVs in the gyrA gene were identified. To conclude, this study highlighted the complexity of recurrent episode cause determination and showed the usefulness of differing SNV identification in both Mtb isolates in such cases. Expected drug susceptibility was the only discriminative factor for recurrent TB episode-causing mycobacterial strains, while no differences between reactivation and reinfection sample groups could be identified.
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    Genotypic and phenotypic comparison of drug resistance profiles of clinical multidrug-resistant Mycobacterium tuberculosis isolates using whole genome sequencing in Latvia
    (2023-12) Vīksna, Anda; Sadovska, Darja; Berge, Iveta; Bogdanova, Ineta; Vaivode, Annija; Freimane, Lauma; Norvaiša, Inga; Ozere, Iveta; Ranka, Renāte; Rīga Stradiņš University
    Background: Multidrug-resistant tuberculosis (MDR–TB) remains a major public health problem in many high tuberculosis (TB) burden countries. Phenotypic drug susceptibility testing (DST) take several weeks or months to result, but line probe assays and Xpert/Rif Ultra assay detect a limited number of resistance conferring gene mutations. Whole genome sequencing (WGS) is an advanced molecular testing method which theoretically can predict the resistance of M. tuberculosis (Mtb) isolates to all anti-TB agents through a single analysis. Methods: Here, we aimed to identify the level of concordance between the phenotypic and WGS-based genotypic drug susceptibility (DS) patterns of MDR–TB isolates. Overall, data for 12 anti-TB medications were analyzed. Results: In total, 63 MDR–TB Mtb isolates were included in the analysis, representing 27.4% of the total number of MDR–TB cases in Latvia in 2012–2014. Among them, five different sublineages were detected, and 2.2.1 (Beijing group) and 4.3.3 (Latin American-Mediterranean group) were the most abundant. There were 100% agreement between phenotypic and genotypic DS pattern for isoniazid, rifampicin, and linezolid. High concordance rate (> 90%) between phenotypic and genotypic DST results was detected for ofloxacin (93.7%), pyrazinamide (93.7%) and streptomycin (95.4%). Phenotypic and genotypic DS patterns were poorly correlated for ethionamide (agreement 56.4%), ethambutol (85.7%), amikacin (82.5%), capreomycin (81.0%), kanamycin (85.4%), and moxifloxacin (77.8%). For capreomycin, resistance conferring mutations were not identified in several phenotypically resistant isolates, and, in contrary, for ethionamide, ethambutol, amikacin, kanamycin, and moxifloxacin the resistance-related mutations were identified in several phenotypically sensitive isolates. Conclusions: WGS is a valuable tool for rapid genotypic DST for all anti-TB agents. For isoniazid and rifampicin phenotypic DST potentially can be replaced by genotypic DST based on 100% agreement between the tests. However, discrepant results for other anti-TB agents limit their prescription based solely on WGS data. For clinical decision, at the current level of knowledge, there is a need for combination of genotypic DST with modern, validated phenotypic DST methodologies for those medications which did not showed 100% agreement between the methods.
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    Unraveling tuberculosis patient cluster transmission chains : integrating WGS-based network with clinical and epidemiological insights
    (2024) Sadovska, Darja; Ozere, Iveta; Pole, Ilva; Ķimsis, Jānis; Vaivode, Annija; Vīksna, Anda; Norvaiša, Inga; Bogdanova, Ineta; Ulanova, Viktorija; Čapligina, Valentīna; Bandere, Dace; Ranka, Renāte; Department of Infectology; Department of Pharmaceutical Chemistry
    BACKGROUND: Tuberculosis remains a global health threat, and the World Health Organization reports a limited reduction in disease incidence rates, including both new and relapse cases. Therefore, studies targeting tuberculosis transmission chains and recurrent episodes are crucial for developing the most effective control measures. Herein, multiple tuberculosis clusters were retrospectively investigated by integrating patients' epidemiological and clinical information with median-joining networks recreated based on whole genome sequencing (WGS) data of Mycobacterium tuberculosis isolates. METHODS: Epidemiologically linked tuberculosis patient clusters were identified during the source case investigation for pediatric tuberculosis patients. Only M. tuberculosis isolate DNA samples with previously determined spoligotypes identical within clusters were subjected to WGS and further median-joining network recreation. Relevant clinical and epidemiological data were obtained from patient medical records. RESULTS: We investigated 18 clusters comprising 100 active tuberculosis patients 29 of whom were children at the time of diagnosis; nine patients experienced recurrent episodes. M. tuberculosis isolates of studied clusters belonged to Lineages 2 (sub-lineage 2.2.1) and 4 (sub-lineages 4.3.3, 4.1.2.1, 4.8, and 4.2.1), while sub-lineage 4.3.3 (LAM) was the most abundant. Isolates of six clusters were drug-resistant. Within clusters, the maximum genetic distance between closely related isolates was only 5-11 single nucleotide variants (SNVs). Recreated median-joining networks, integrated with patients' diagnoses, specimen collection dates, sputum smear microscopy, and epidemiological investigation results indicated transmission directions within clusters and long periods of latent infection. It also facilitated the identification of potential infection sources for pediatric patients and recurrent active tuberculosis episodes refuting the reactivation possibility despite the small genetic distance of ≤5 SNVs between isolates. However, unidentified active tuberculosis cases within the cluster, the variable mycobacterial mutation rate in dormant and active states, and low M. tuberculosis genetic variability inferred precise transmission chain delineation. In some cases, heterozygous SNVs with an allelic frequency of 10-73% proved valuable in identifying direct transmission events. CONCLUSION: The complex approach of integrating tuberculosis cluster WGS-data-based median-joining networks with relevant epidemiological and clinical data proved valuable in delineating epidemiologically linked patient transmission chains and deciphering causes of recurrent tuberculosis episodes within clusters.