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Summary Background A large, double-blind, randomised, placebo-controlled trial of repeat BCG found 49% efficacy against leprosy but no protection against tuberculosis after 6–9 years’ follow-up in 1995. We report here additional follow-up, which resulted in greatly increased tuberculosis case numbers, and allowed subgroup analysis. Methods Nearly 47 000 individuals of all ages living in northern Malawi with a BCG vaccine scar were randomly assigned (1:1) between 1986 and 1989 to receive a second BCG or placebo. The investigators and project staff remained masked to all interventions. Enhanced passive surveillance ensured ascertainment of tuberculosis and leprosy to the end of 2018. Tuberculosis case definitions included rigorous microbiological or histological confirmation. Prespecified subgroup analyses were by tuberculosis type, age at vaccination, time since vaccination, previous tuberculin reactivity, HIV status and Mycobacterium tuberculosis lineage. The original trial is registered with ISRCTN registry, ISRCTN11311670. Findings In follow-up until Dec 31, 2018, 824 participants had developed tuberculosis, including 786 with pulmonary disease, of whom 383 (63%) of 607 with known HIV status were HIV positive. There was no effect of a second BCG overall (odds ratio [OR] 0·92; 95% CI 0·80–1·05), or for pulmonary (0·93; 0·81–1·07), or lymph node tuberculosis (0·60; 0·31–1·17). The OR was lower for those with known HIV-negative tuberculosis (0·77; 0·59–1·00), for those vaccinated as children (aged

Understanding host and pathogen factors that influence tuberculosis (TB) transmission can inform strategies to eliminate the spread of Mycobacterium tuberculosis (Mtb). Determining transmission links between cases of TB is complicated by a long and variable latency period and undiagnosed cases, although methods are improving through the application of probabilistic modelling and whole-genome sequence analysis. Using a large dataset of 1857 whole-genome sequences and comprehensive metadata from Karonga District, Malawi, over 19 years, we reconstructed Mtb transmission networks using a two-step Bayesian approach that identified likely infector and recipient cases, whilst robustly allowing for incomplete case sampling. We investigated demographic and pathogen genomic variation associated with transmission and clustering in our networks. We found that whilst there was a significant decrease in the proportion of infectors over time, we found higher transmissibility and large transmission clusters for lineage 2 (Beijing) strains. By performing evolutionary convergence testing (phyC) and genome-wide association analysis (GWAS) on transmitting versus non-transmitting cases, we identified six loci, PPE54, accD2, PE_PGRS62, rplI, Rv3751 and Rv2077c, that were associated with transmission. This study provides a framework for reconstructing large-scale Mtb transmission networks. We have highlighted potential host and pathogen characteristics that were linked to increased transmission in a high-burden setting and identified genomic variants that, with validation, could inform further studies into transmissibility and TB eradication.

Understanding host and pathogen factors that influence tuberculosis (TB) transmission can inform strategies to eliminate the spread of Mycobacterium tuberculosis (Mtb). Determining transmission links between cases of TB is complicated by a long and variable latency period and undiagnosed cases, although methods are improving through the application of probabilistic modelling and whole-genome sequence analysis. Using a large dataset of 1857 whole-genome sequences and comprehensive metadata from Karonga District, Malawi, over 19 years, we reconstructed Mtb transmission networks using a two-step Bayesian approach that identified likely infector and recipient cases, whilst robustly allowing for incomplete case sampling. We investigated demographic and pathogen genomic variation associated with transmission and clustering in our networks. We found that whilst there was a significant decrease in the proportion of infectors over time, we found higher transmissibility and large transmission clusters for lineage 2 (Beijing) strains. By performing evolutionary convergence testing (phyC) and genome-wide association analysis (GWAS) on transmitting versus non-transmitting cases, we identified six loci, PPE54, accD2, PE_PGRS62, rplI, Rv3751 and Rv2077c, that were associated with transmission. This study provides a framework for reconstructing large-scale Mtb transmission networks. We have highlighted potential host and pathogen characteristics that were linked to increased transmission in a high-burden setting and identified genomic variants that, with validation, could inform further studies into transmissibility and TB eradication.

Background Mixed, polyclonal Mycobacterium tuberculosis infection occurs in natural populations. Developing an effective method for detecting such cases is important in measuring the success of treatment and reconstruction of transmission between patients. Using whole genome sequence (WGS) data, we assess two methods for detecting mixed infection: (i) a combination of the number of heterozygous sites and the proportion of heterozygous sites to total SNPs, and (ii) Bayesian model-based clustering of allele frequencies from sequencing reads at heterozygous sites. Results In silico and in vitro artificially mixed and known pure M. tuberculosis samples were analysed to determine the specificity and sensitivity of each method. We found that both approaches were effective in distinguishing between pure strains and mixed infection where there was relatively high (> 10%) proportion of a minor strain in the mixture. A large dataset of clinical isolates (n = 1963) from the Karonga Prevention Study in Northern Malawi was tested to examine correlations with patient characteristics and outcomes with mixed infection. The frequency of mixed infection in the population was found to be around 10%, with an association with year of diagnosis, but no association with age, sex, HIV status or previous tuberculosis. Conclusions Mixed Mycobacterium tuberculosis infection was identified in silico using whole genome sequence data. The methods presented here can be applied to population-wide analyses of tuberculosis to estimate the frequency of mixed infection, and to identify individual cases of mixed infections. These cases are important when considering the evolution and transmission of the disease, and in patient treatment. Electronic supplementary material The online version of this article (10.1186/s12864-018-4988-z) contains supplementary material, which is available to authorized users.

To improve understanding of the factors influencing tuberculosis transmission and the role of pathogen variation, we sequenced all available specimens from patients diagnosed over 15 years in a whole district in Malawi. Mycobacterium tuberculosis lineages were assigned and transmission networks constructed, allowing ≤10 single nucleotide polymorphisms (SNPs) difference. We defined disease as due to recent infection if the network-determined source was within 5 years, and assessed transmissibility from forward transmissions resulting in disease. High-quality sequences were available for 1687 disease episodes (72% of all culture-positive episodes): 66% of patients linked to at least one other patient. The between-patient mutation rate was 0.26 SNPs/year (95% CI 0.21–0.31). We showed striking differences by lineage in the proportion of disease due to recent transmission and in transmissibility (highest for lineage-2 and lowest for lineage-1) that were not confounded by immigration, HIV status or drug resistance. Transmissions resulting in disease decreased markedly over time. DOI: http://dx.doi.org/10.7554/eLife.05166.001, eLife digest Tuberculosis is an important public health threat around the globe and is particularly common in developing countries. It is difficult to control the spread of the disease because the bacteria that cause it can spread when an infected individual coughs or sneezes. It may take years for an infected individual to develop symptoms of tuberculosis so it can be hard to trace the source of an outbreak, and people infected with HIV are particularly susceptible to the disease. The bacterium that causes the majority of cases of tuberculosis is called Mycobacterium tuberculosis. There are several different varieties or ‘lineages’ of M. tuberculosis, and it is thought that they may vary in their ability to spread and cause disease. However, the results of previous studies have been inconsistent and there also seems to be a lot of variation between strains within the same lineage. In this study, Guerra-Assunção et al. used an approach called whole genome sequencing alongside more traditional methods to study the spread of tuberculosis in Malawi. They sequenced the genomes of every available sample of M. tuberculosis collected from patients in the Karonga district of Malawi over a 15-year period. This produced high-quality DNA sequence data about the bacteria responsible for almost 1700 cases of disease. Using this massive amount of data, Guerra-Assunção et al. constructed networks that showed how the bacteria had spread in the community. This revealed that there were differences between the ability of the various M. tuberculosis lineages to cause disease and to spread in communities. For example, lineage 1 was less likely than the other lineages to cause disease soon after infecting an individual and was less able to spread. The data also show that the proportion of cases of disease due to recent infection declined substantially during the 15-year period. This indicates that the tuberculosis and HIV control programmes in the area have been successful. Guerra-Assunção et al.'s findings show that it is possible to understand how tuberculosis is transmitted on a large scale. The next challenge is to understand why the lineages differ in their ability to cause disease and spread between individuals. DOI: http://dx.doi.org/10.7554/eLife.05166.002

Background. Recurrent tuberculosis is a major health burden and may be due to relapse with the original strain or reinfection with a new strain. Methods. In a population-based study in northern Malawi, patients with tuberculosis diagnosed from 1996 to 2010 were actively followed after the end of treatment. Whole-genome sequencing with approximately 100-fold coverage was performed on all available cultures. Results of IS6110 restriction fragment-length polymorphism analyses were available for cultures performed up to 2008. Results. Based on our data, a difference of ≤10 single-nucleotide polymorphisms (SNPs) was used to define relapse, and a difference of >100 SNPs was used to define reinfection. There was no evidence of mixed infections among those classified as reinfections. Of 1471 patients, 139 had laboratory-confirmed recurrences: 55 had relapse, and 20 had reinfection; for 64 type of recurrence was unclassified. Almost all relapses occurred in the first 2 years. Human immunodeficiency virus infection was associated with reinfection but not relapse. Relapses were associated with isoniazid resistance, treatment before 2007, and lineage-3 strains. We identified several gene variants associated with relapse. Lineage-2 (Beijing) was overrepresented and lineage-1 underrepresented among the reinfecting strains (P = .004). Conclusions. While some of the factors determining recurrence depend on the patient and their treatment, differences in the Mycobacterium tuberculosis genome appear to have a role in both relapse and reinfection.