Distribution and Clonality of drug-resistant tuberculosis in South Africa

Tuberculin skin test surveys and the Annual Risk of Tuberculous Infection in school children in Northern KwaZulu-Natal

Tuberculin skin test surveys in primary school children can be used to quantify Mycobacterium tuberculosis transmission at community level. KwaZulu-Natal province, South Africa, is home to 11.5 million people and suffers a burden of tuberculosis disease that is among the highest in the world. The last tuberculin survey in the province was undertaken in 1979. We performed a tuberculin skin test survey nested within a demographic and health household surveillance programme in Northern KwaZulu-Natal. We enrolled children aged between six and eight years of age attending primary schools in this community. Mixture analysis was used to determine tuberculin skin test thresholds and the Annual Risk of Tuberculous Infection derived from age at testing and infection prevalence. The Community Infection Ratio, a measure of the relative importance of within-household and community transmission, was calculated from data on tuberculin positivity disaggregated by household tuberculosis contact. Between June and December 2013, we obtained tuberculin skin test results on 1240 children. Mixture analysis proved unstable, suggesting two potential thresholds for test positivity. Using a threshold of ≥10mm or treating all non zero reactions as positive yielded estimates of the Annual Risk of Tuberculous Infection of 1.7% (1.4-2.1%) or 2.4% (2.0-3.0%). Using the same thresholds and including children reported to be receiving TB treatment as cases, resulted in estimates of 2.0% (1.6-2.5%) or 2.7% (2.2-3.3%). The Community Infection Ratio was 0.58 (0.33-1.01). The force of infection in this community is lower than that observed in Western Cape province, South Africa, but higher than that observed in community settings in most other parts of the world. Children in this community are commonly infected with Mycobacterium tuberculosis outside the home. Interventions to interrupt transmission are urgently needed.

Population structure and spatial distribution of Mycobacterium tuberculosis in Ethiopia

Ethiopia is one of the countries with a high tuberculosis (TB) burden, yet little is known about the spatial distribution of Mycobacterium tuberculosis (Mtb) lineages. This study identifies the spoligotyping of 1735 archived Mtb isolates from the National Drug Resistance Survey, collected between November 2011 and June 2013, to investigate Mtb population structure and spatial distribution. Spoligotype International Types (SITs) and lineages were retrieved from online databases. The distribution of lineages was evaluated using Fisher's exact test and logistic regression models. The Global Moran's Index and Getis-Ord Gi statistic were utilized to identify hotspot areas. Our results showed that spoligotypes could be interpreted and led to 4 lineages and 283 spoligotype patterns in 91% of the isolates, including 4% of those with multidrug/rifampicin resistance (MDR/RR) TB. The identified Mtb lineages were lineage 1 (1.8%), lineage 3 (25.9%), lineage 4 (70.6%) and lineage 7 (1.6%). The proportion of lineages 3 and 4 varied by regions, with lineage 3 being significantly greater than lineage 4 in reports from Gambella (AOR = 4.37, P < 0.001) and Tigray (AOR = 3.44, P = 0.001) and lineage 4 being significantly higher in Southern Nations Nationalities and Peoples Region (AOR = 1.97, P = 0.026) than lineage 3. Hotspots for lineage 1 were located in eastern Ethiopia, while a lineage 7 hotspot was identified in northern and western Ethiopia. The five prevalent spoligotypes, which were SIT149, SIT53, SIT25, SIT37 and SIT26 account for 42.8% of all isolates under investigation, while SIT149, SIT53 and SIT21 account for 52-57.8% of drug-resistant TB cases. TB and drug resistant TB are mainly caused by lineages 3 and 4, and significant proportions of the prevalent spoligotypes also influence drug-resistant TB and the total TB burden. Regional variations in lineages may result from both local and cross-border spread.

Determining the risk-factors for molecular clustering of drug-resistant tuberculosis in South Africa

BACKGROUND

Drug-resistant tuberculosis (DR-TB) epidemic is driven mainly by the effect of ongoing transmission. In high-burden settings such as South Africa (SA), considerable demographic and geographic heterogeneity in DR-TB transmission exists. Thus, a better understanding of risk-factors for clustering can help to prioritise resources to specifically targeted high-risk groups as well as areas that contribute disproportionately to transmission.

METHODS

The study analyzed potential risk-factors for recent transmission in SA, using data collected from a sentinel molecular surveillance of DR-TB, by comparing demographic, clinical and epidemiologic characteristics with clustering and cluster sizes. A genotypic cluster was defined as two or more patients having identical patterns by the two genotyping methods used. Clustering was used as a proxy for recent transmission. Descriptive statistics and multinomial logistic regression were used.

RESULT

The study identified 277 clusters, with cluster size ranging between 2 and 259 cases. The majority (81.6%) of the clusters were small (2-5 cases) with few large (11-25 cases) and very large (≥ 26 cases) clusters identified mainly in Western Cape (WC), Eastern Cape (EC) and Mpumalanga (MP). In a multivariable model, patients in clusters including 11-25 and ≥ 26 individuals were more likely to be infected by Beijing family, have XDR-TB, living in Nelson Mandela Metro in EC or Umgungunglovo in Kwa-Zulu Natal (KZN) provinces, and having history of imprisonment. Individuals belonging in a small genotypic cluster were more likely to infected with Rifampicin resistant TB (RR-TB) and more likely to reside in Frances Baard in Northern Cape (NC).

CONCLUSION

Sociodemographic, clinical and bacterial risk-factors influenced rate of Mycobacterium tuberculosis (M. tuberculosis) genotypic clustering. Hence, high-risk groups and hotspot areas for clustering in EC, WC, KZN and MP should be prioritized for targeted intervention to prevent ongoing DR-TB transmission.

The Detection of Mutations and Genotyping of Drug-Resistant Mycobacterium tuberculosis Strains Isolated from Patients in the Rural Eastern Cape Province

Drug-resistant tuberculosis (DR-TB) is still a major public health concern in South Africa. Mutations in M. tuberculosis can cause varying levels of phenotypic resistance to anti-TB medications. There have been no prior studies on gene mutations and the genotyping of DR-TB in the rural Eastern Cape Province; hence, we aimed to identify DR-TB mutations, genetic diversity, and allocated lineages among patients in this area. Using Xpert^® MTB/RIF, we assessed the rifampin resistance of sputum samples collected from 1157 patients suspected of having tuberculosis. GenoType MTBDR plus VER 2.0 was used for the detection of mutations causing resistance to anti-TB medications. The next step was to spoligotype 441 isolates. The most prevalent rifampin resistance-conferring mutations were in rpoB codon S531L in INH-resistant strains; the katG gene at codon S315TB and the inhA gene at codon C-15TB had the most mutations; 54.5% and 24.7%, respectively. In addition, 24.6% of strains showed mutations in both the rpoB and inhA genes, while 69.9% of strains showed mutations in both the katG and rpoB genes. Heteroresistance was seen in 17.9% of all cases in the study. According to spoligotyping analysis, Beijing families predominated. Investigation of the evolutionary lineages of M. tuberculosis isolates can be carried out using the information provided by the study's diversity of mutations. In locations wherein these mutations have been discovered, decision-making regarding the standardization of treatment regimens or individualized treatment may be aided by the detection frequency of rpoB, katG, and inhA mutations in various study areas.

Spatial Distribution of Drug-Resistant Mycobacterium tuberculosis Infections in Rural Eastern Cape Province of South Africa

Tuberculosis (TB), an infectious airborne disease caused by Mycobacterium tuberculosis (Mtb), is a serious public health threat reported as the leading cause of morbidity and mortality worldwide. South Africa is a high-TB-burden country with TB being the highest infectious disease killer. This study investigated the distribution of Mtb mutations and spoligotypes in rural Eastern Cape Province. The Mtb isolates included were 1157 from DR-TB patients and analysed by LPA followed by spoligotyping of 441 isolates. The distribution of mutations and spoligotypes was done by spatial analysis. The rpoB gene had the highest number of mutations. The distribution of rpoB and katG mutations was more prevalent in four healthcare facilities, inhA mutations were more prevalent in three healthcare facilities, and heteroresistant isolates were more prevalent in five healthcare facilities. The Mtb was genetically diverse with Beijing more prevalent and largely distributed. Spatial analysis and mapping of gene mutations and spoligotypes revealed a better picture of distribution.

Variants in Bedaquiline-Candidate-Resistance Genes: Prevalence in Bedaquiline-Naive Patients, Effect on MIC, and Association with Mycobacterium tuberculosis Lineage

Studies have shown that variants in bedaquiline-resistance genes can occur in isolates from bedaquiline-naive patients. We assessed the prevalence of variants in all bedaquiline-candidate-resistance genes in bedaquiline-naive patients, investigated the association between these variants and lineage, and the effect on phenotype. We used whole-genome sequencing to identify variants in bedaquiline-resistance genes in isolates from 509 bedaquiline treatment naive South African tuberculosis patients. A phylogenetic tree was constructed to investigate the association with the isolate lineage background. Bedaquiline MIC was determined using the UKMYC6 microtiter assay. Variants were identified in 502 of 509 isolates (98.6%), with the highest (85%) prevalence of variants in the Rv0676c (mmpL5) gene. We identified 36 unique variants, including 19 variants not reported previously. Only four isolates had a bedaquiline MIC equal to or above the epidemiological cut-off value of 0.25 μg/mL. Phylogenetic analysis showed that 14 of the 15 variants observed more than once occurred monophyletically in one Mycobacterium tuberculosis (sub)lineage. The bedaquiline MIC differed between isolates belonging to lineage 2 and 4 (Fisher's exact test, P = 0.0004). The prevalence of variants in bedaquiline-resistance genes in isolates from bedaquiline-naive patients is high, but very few (<2%) isolates were phenotypically resistant. We found an association between variants in bedaquiline resistance genes and Mycobacterium tuberculosis (sub)lineage, resulting in a lineage-dependent difference in bedaquiline phenotype. Future studies should investigate the impact of the presence of variants on bedaquiline-resistance acquisition and treatment outcome.