Prevalence and Risk Factors of Subclinical Tuberculosis in a Low-Incidence Setting in China

Objectives: Subclinical tuberculosis (TB) represents a substantial proportion of individuals with TB disease, although limited evidence is available to understand the epidemiological characteristics of these cases. We aimed to explore the prevalence of subclinical patients with TB and identify the underlying association between the subclinical TB cases in the study setting and the Beijing genotype.Methods: A retrospective study was conducted among patients with incident TB at the Fifth People’s Hospital of Suzhou between January and December 2018. A total of 380 patients with TB were included in our analysis.Results: Of the 380 patients, 81.8% were active TB cases, whereas the other 18.2% were subclinical TB cases. Compared with patients aged 65 years and older, the risk of having subclinical TB is higher among younger patients. The use of smear, culture, and Xpert identified 3, 16, and 13 subclinical TB cases, respectively. When using a combination of positive culture and Xpert results, the sensitivity improved to 33.3%. In addition, the neutrophil-to-lymphocyte ratio was significantly elevated in the active TB group compared with that in the subclinical TB group. We also observed that the proportion of the Beijing genotype in the subclinical TB group was significantly lower than that in the active TB group.Conclusion: To conclude, our data demonstrate that approximately one-fifth of patients with TB were subclinical in Suzhou. Mycobacterium tuberculosis could be detected by the existing microbiologic diagnostics in one-third of patients with subclinical TB. The patients with subclinical TB are more prone to having low neutrophil-to-lymphocyte ratio values than those with active TB. Additionally, non-Beijing genotype strains are associated with subclinical TB.

MDR and Pre-XDR Clinical Mycobacterium tuberculosis Beijing Strains: Assessment of Virulence and Host Cytokine Response in Mice Infectious Model

Mycobacterium tuberculosis Beijing genotype associated with drug resistance is a growing public health problem worldwide. The aim of this study was the assessment of virulence for C57BL/6 mice after infection by clinical M. tuberculosis strains 267/47 and 120/26, which belong to the modern sublineages B0/W148 and Central Asia outbreak of the Beijing genotype, respectively. The sublineages were identified by the analysis of the strains’ whole-genomes. The strains 267/47 and 120/26 were characterized as agents of pre-extensively drug-resistant (pre-XDR) and multidrug-resistant (MDR) tuberculosis, respectively. Both clinical strains were slow-growing in 7H9 broth compared to the M. tuberculosis H37Rv strain. The survival rates of C57BL/6 mice infected by 267/47, 120/26, and H37Rv on the 150th day postinfection were 10%, 40%, and 70%, respectively. Mycobacterial load in the lungs, spleen, and liver was higher and histopathological changes were more expressed for mice infected by the 267/47 strain compared to those infected by the 120/26 and H37Rv strains. The cytokine response in the lungs of C57BL/6 mice after infection with the 267/47, 120/26, and H37Rv strains was different. Notably, proinflammatory cytokine genes Il-1α, Il-6, Il-7, and Il-17, as well as anti-inflammatory genes Il-6 and Il-13, were downregulated after an infection caused by the 267/47 strain compared to those after infection with the H37Rv strain.

Transborder molecular analysis of MDR tuberculosis dynamics in Mongolia and Eastern Siberia, Russia

Mongolia and Eastern Siberia, Russia are border regions in Asia with high incidence of tuberculosis (TB). In this study, we aimed to investigate MDR -TB transborder transmission with a focus on endemic and epidemic Mycobacterium tuberculosis clones and drug resistance patterns. M. tuberculosis strains (291 from Mongolia and 754 from Russia) were collected within cross-sectional population-based surveys in 2010-2016. DNA was genotyped in 24 MIRU-VNTR loci and by PCR testing of the key SNP markers to discriminate within Beijing genotype. In total, 1045 isolates were divided into 435 MIRU-types that were assigned to Lineage 2 (Beijing isolates) and Lineage 4 (Ural, Haarlem, Latin-American-Mediterranean [LAM], S, and unclassified isolates). Beijing genotype was dominant in both countries, but most of Russian and all Mongolian Beijing strains belonged to different subtypes of the modern Beijing sublineage with only negligible overlap between the two countries. In particular, the Beijing types #342-32, #3819-32, #1773-32 (Asian African 2 group) were found only in Mongolia. LAM was the most common non-Beijing genotype (11.0% in Mongolia and 14.7% in Russia) and its isolates mostly belonged to LAM-RUS branch. MDR rate was higher in Russia compared to Mongolia among newly diagnosed patients: 29.4% versus 4.2% (p < 0.001) but similar and high in the retreatment subgroups (65.8% and 67.4%, respectively). In Russian collection, a higher MDR rate was observed in (i) Beijing compared to non-Beijing (47.5% versus 38.8%, p = 0.03), (ii) Beijing B0/W148 subtype compared to Beijing Central Asian/Russian subtype (64.5% versus 39.3%, p <0.001). In Mongolia, MDR rate was similar in Beijing (29.7%) and non-Beijing (27.5%) genotypes. In conclusion, population structures of the Beijing genotype in Mongolia and Russian borderline regions differ significantly including specific patterns of drug resistance. In contrast, largely overlapping LAM subtypes may correlate with historical endemic circulation of the LAM-RUS branch in Northern Eurasia.

Molecular and genetic analysis of Mycobacterium tuberculosis population in the Vologda Region with low tuberculosis incidence

The Vologda Region is characterized by a relatively calm epidemic situation for tuberculosis in Russia: the incidence rate in 2010—2018 is decreased from 45.2 to 15.8 per 100 thousand of the population (44.4 in Russia). However, the proportion of patients with multiple drug resistance (MDR) of the pathogen increased from 12.1% in 2016 to 23.7% in 2018. The aim of the study was to characterize the genetic structure of the M. tuberculosis population and identify the main genotypes associated with the primary multidrug resistance of the pathogen in the Vologda Region. A total of 82 strains of M. tuberculosis isolated in 2018 from newly diagnosed tuberculosis patients were studied. Drug susceptibility testing was performed using the standard method of absolute concentration and BACTEC MGIT 960 kit. M. tuberculosis strains were assigned to the Beijing genotype and its main subtypes based on the analysis of specific markers. The Beijing strains were subtyped by the MIRU-VNTR method (24 standard loci), calculating the Hunter-Gaston Discriminatory Index (HGDI). Other strains of the non-Beijing group were spoligotyped. The majority of the strains were of the Beijing genotype (62.2%; 51 of 82). The most numerous cluster was Central Asian/Russian (41.5%; 34 of 82 strains). The shares of the Central Asia Outbreak (CAO) subtype and cluster B0/W148 amounted to 8.5% and 7.3%, respectively. The non-Beijing strains belonged to the genetic families T (11%; 9 of 82), LAM (11%), Haarlem (6.1%), and Ural (4.9%). Among 82 M. tuberculosis isolates, 33 (40.2%) MDR strains were identified, counting 27 of the Beijing genotype, including those of the Central Asian/Russian — 18 (66.7%), B0/W148 and CAO — 4 each (14.8%) clusters. MIRU-VNTR typing of 51 Beijing strains revealed 22 profiles (HGDI = 0.852); the largest clusters were 94-32 (35.3%) and 95-32 (15.7%), which included strains Central Asian/Russian and CAO. Four strains of genotype B0/W148 belonged to cluster 100-32. The loci QUB26 (HGDI = 0.493) and MIRU26 (HGDI = 0.388) had the highest polymorphism. For the first time, a molecular genetic study carried out in the Vologda region revealed the heterogeneity of the M. tuberculosis population with strains of the Beijing genotype dominated. At the same time, the share of the associated with MDR, epidemiologically and clinically significant cluster Beijing B0/W148, well defined in Russia and abroad, was only 7.3%, which is significantly less than in other regions of the Northwestern Federal District of the Russian Federation (~19%). Concurrent, representatives of the Central Asian/Russian cluster of the Beijing genotype prevailed in the structure of genotypes and among MDR M. tuberculosis strains.

Distribution and Clonality of drug-resistant tuberculosis in South Africa

Background Studies have shown that drug-resistant tuberculosis (DR-TB) in South Africa (SA) is clonal and is caused mostly by transmission. Identifying transmission chains is important in controlling DR-TB. This study reports on the sentinel molecular surveillance data of Rifampicin-Resistant (RR) TB in SA, aiming to describe the RR-TB strain population and the estimated transmission of RR-TB cases. Method RR-TB isolates collected between 2014 and 2018 from eight provinces were genotyped using combination of spoligotyping and 24-loci mycobacterial interspersed repetitive-units-variable-number tandem repeats (MIRU-VNTR) typing. Results Of the 3007 isolates genotyped, 301 clusters were identified. Cluster size ranged between 2 and 270 cases. Most of the clusters (247/301; 82.0%) were small in size (< 5 cases), 12.0% (37/301) were medium sized (5–10 cases), 3.3% (10/301) were large (11–25 cases) and 2.3% (7/301) were very large with 26–270 cases. The Beijing genotype was responsible for majority of RR-TB cases in Western and Eastern Cape, while the East-African-Indian-Somalian (EAI1_SOM) genotype accounted for a third of RR-TB cases in Mpumalanga. The overall proportion of RR-TB cases estimated to be due to transmission was 42%, with the highest transmission-rate in Western Cape (64%) and the lowest in Northern Cape (9%). Conclusion Large clusters contribute to the burden of RR-TB in specific geographic areas such as Western Cape, Eastern Cape and Mpumalanga, highlighting the need for community-wide interventions. Most of the clusters identified in the study were small, suggesting close contact transmission events, emphasizing the importance of contact investigations and infection control as the primary interventions in SA.