Project description:Mycobacterium tuberculosis is characterised by limited genomic diversity, which makes the application of whole genome sequencing particularly attractive for clinical and epidemiological investigation. However, in order to confidently infer transmission events, an accurate knowledge of the rate of change in the genome over relevant timescales is required.We attempted to estimate a molecular clock by sequencing 199 isolates from epidemiologically linked tuberculosis cases, collected in the Netherlands spanning almost 16 years.Multiple analyses support an average mutation rate of ~0.3 SNPs per genome per year. However, all analyses revealed a very high degree of variation around this mean, making the confirmation of links proposed by epidemiology, and inference of novel links, difficult. Despite this, in some cases, the phylogenetic context of other strains provided evidence supporting the confident exclusion of previously inferred epidemiological links.This in-depth analysis of the molecular clock revealed that it is slow and variable over short time scales, which limits its usefulness in transmission studies. However, the superior resolution of whole genome sequencing can provide the phylogenetic context to allow the confident exclusion of possible transmission events previously inferred via traditional DNA fingerprinting techniques and epidemiological cluster investigation. Despite the slow generation of variation even at the whole genome level we conclude that the investigation of tuberculosis transmission will benefit greatly from routine whole genome sequencing.
Project description:Genomics is increasingly being used to investigate disease outbreaks, but an important question remains unanswered--how well do genomic data capture known transmission events, particularly for pathogens with long carriage periods or large within-host population sizes? Here we present a novel Bayesian approach to reconstruct densely sampled outbreaks from genomic data while considering within-host diversity. We infer a time-labeled phylogeny using Bayesian evolutionary analysis by sampling trees (BEAST), and then infer a transmission network via a Monte Carlo Markov chain. We find that under a realistic model of within-host evolution, reconstructions of simulated outbreaks contain substantial uncertainty even when genomic data reflect a high substitution rate. Reconstruction of a real-world tuberculosis outbreak displayed similar uncertainty, although the correct source case and several clusters of epidemiologically linked cases were identified. We conclude that genomics cannot wholly replace traditional epidemiology but that Bayesian reconstructions derived from sequence data may form a useful starting point for a genomic epidemiology investigation.
Project description:BACKGROUND: Tuberculosis remains common in Singapore, increasing in incidence since 2008. We attempted to determine the molecular epidemiology of Mycobacterium tuberculosis complex (MTC) isolates locally, identifying major circulating genotypes and obtaining a glimpse of transmission dynamics. METHODOLOGY: Non-duplicate MTC isolates archived between 2006 and 2012 at the larger clinical tuberculosis laboratory in Singapore were sampled for spoligotyping and MIRU-VNTR typing, with case data obtained from the Singapore Tuberculosis Elimination Program registry database. Isolates between 2008 and 2012 were selected because of either multidrug-resistance or potential epidemiological linkage, whereas earlier isolates were randomly selected. Separate analyses were performed for the early (2006-2007) and later (2008-2012) study phases in view of potential selection bias. PRINCIPAL FINDINGS: A total of 1,612 MTC isolates were typed, constituting 13.1% of all culture-positive tuberculosis cases during this period. Multidrug-resistance was present in 91 (5.6%) isolates - higher than the national prevalence in view of selection bias. The majority of isolates belonged to the Beijing (45.8%) and EAI (22.8%) lineages. There were 347 (30.7%) and 133 (27.5%) cases clustered by combined spoligotyping and MIRU-VNTR typing from the earlier and later phases respectively. Patients within these clusters tended to be of Chinese ethnicity, Singapore resident, and have isolates belonging to the Beijing lineage. A review of prior contact investigation results for all patients with clustered isolates failed to reveal epidemiological links for the majority, suggesting either unknown transmission networks or inadequate specificity of the molecular typing methods in a country with a moderate incidence of tuberculosis. CONCLUSION: Our work demonstrates that Singapore has a large and heterogeneous distribution of MTC strains, and with possible cross-transmission over the past few years based on our molecular typing results. A universal MTC typing program coupled with enhanced contact investigations may be useful in further understanding the transmission dynamics of tuberculosis locally.
Project description:Recently developed molecular techniques have revolutionized the epidemiology of tuberculosis. Multiple studies have used these tools to examine the population structure of Mycobacterium tuberculosis isolates in different communities. The distributions of clusters of M. tuberculosis isolates in these settings may variously reflect social mixing patterns or the differential fitness of specific clones of the organism. We developed an individual-based microsimulation of tuberculosis transmission to explore social and demographic determinants of cluster distribution and to observe the effect of transmission dynamics on the empiric data from molecular epidemiologic studies. Our results demonstrate that multiple host-related factors contribute to wide variation in cluster distributions even when all strains of the organism are assumed to be equally transmissible. These host characteristics include interventions such as chemotherapy, vaccination and chemoprophylaxis, HIV prevalence, the age structure of the population, and the prevalence of latent tuberculosis infection. We consider the implications of these results for the interpretation of cluster studies of M. tuberculosis as well as the more general application of microsimulation models to infectious disease epidemiology.
Project description:<h4>Rationale</h4>Current tools available to study the molecular epidemiology of tuberculosis do not provide information about the directionality and sequence of transmission for tuberculosis cases occurring over a short period of time, such as during an outbreak. Recently, whole genome sequencing has been used to study molecular epidemiology of Mycobacterium tuberculosis over short time periods.<h4>Objective</h4>To describe the microevolution of M. tuberculosis during an outbreak caused by one drug-susceptible strain. METHOD AND MEASUREMENTS: We included 9 patients with tuberculosis diagnosed during a period of 22 months, from a population-based study of the molecular epidemiology in San Francisco. Whole genome sequencing was performed using Illumina's sequencing by synthesis technology. A custom program written in Python was used to determine single nucleotide polymorphisms which were confirmed by PCR product Sanger sequencing.<h4>Main results</h4>We obtained an average of 95.7% (94.1-96.9%) coverage for each isolate and an average fold read depth of 73 (1 to 250). We found 7 single nucleotide polymorphisms among the 9 isolates. The single nucleotide polymorphisms data confirmed all except one known epidemiological link. The outbreak strain resulted in 5 bacterial variants originating from the index case A1 with 0-2 mutations per transmission event that resulted in a secondary case.<h4>Conclusions</h4>Whole genome sequencing analysis from a recent outbreak of tuberculosis enabled us to identify microevolutionary events observable during transmission, to determine 0-2 single nucleotide polymorphisms per transmission event that resulted in a secondary case, and to identify new epidemiologic links in the chain of transmission.
Project description:Natural history studies of tuberculosis (TB) have revealed a spectrum of clinical outcomes after exposure to Mycobacterium tuberculosis, the cause of TB. Not all individuals exposed to the bacterium will become diseased and depending on the infection pressure, many will remain infection-free. Intriguingly, complete resistance to infection is observed in some individuals (termed resisters) after intense, continuing M. tuberculosis exposure. After successful infection, the majority of individuals will develop latent TB infection (LTBI). This infection state is currently (and perhaps imperfectly) defined by the presence of a positive tuberculin skin test (TST) and/or interferon gamma release assay (IGRA), but no detectable clinical disease symptoms. The majority of healthy individuals with LTBI are resistant to clinical TB, indicating that infection is remarkably well-contained in these non-progressors. The remaining 5-15% of LTBI positive individuals will progress to active TB. Epidemiological investigations have indicated that the host genetic component contributes to these infection and disease phenotypes, influencing both susceptibility and resistance. Elucidating these genetic correlates is therefore a priority as it may translate to new interventions to prevent, diagnose or treat TB. The most successful approaches in resistance/susceptibility investigation have focused on specific infection and disease phenotypes and the resister phenotype may hold the key to the discovery of actionable genetic variants in TB infection and disease. This review will not only discuss lessons from epidemiological studies, but will also focus on the contribution of epidemiology and functional genetics to human genetic resistance to M. tuberculosis infection and disease.
Project description:Pathogen genetics is already a mainstay of public health investigation and control efforts; now advances in technology make it possible to investigate the role of human genetic variation in the epidemiology of infectious diseases. To describe trends in this field, we analyzed articles that were published from 2001 through 2010 and indexed by the HuGE Navigator, a curated online database of PubMed abstracts in human genome epidemiology. We extracted the principal findings from all meta-analyses and genome-wide association studies (GWAS) with an infectious disease-related outcome. Finally, we compared the representation of diseases in HuGE Navigator with their contributions to morbidity worldwide. We identified 3,730 articles on infectious diseases, including 27 meta-analyses and 23 GWAS. The number published each year increased from 148 in 2001 to 543 in 2010 but remained a small fraction (about 7%) of all studies in human genome epidemiology. Most articles were by authors from developed countries, but the percentage by authors from resource-limited countries increased from 9% to 25% during the period studied. The most commonly studied diseases were HIV/AIDS, tuberculosis, hepatitis B infection, hepatitis C infection, sepsis, and malaria. As genomic research methods become more affordable and accessible, population-based research on infectious diseases will be able to examine the role of variation in human as well as pathogen genomes. This approach offers new opportunities for understanding infectious disease susceptibility, severity, treatment, control, and prevention.
Project description:Objective:To analyse the epidemiological trends of tuberculosis in the Siberian and Far Eastern federal districts, the areas with the highest disease burden in the Russian Federation. Methods:We applied principal coordinate analysis to study a total of 68 relevant variables on tuberculosis epidemiology, prevention and control. Data on these variables were collected over 2003-2016 in all 21 regions of the Siberian federal district and Far Eastern federal district (total population: 25.5 million) through the federal and departmental reporting system. We identified the regions with a favourable or unfavourable tuberculosis epidemiological profile and ranked them as low or high priority for specific interventions. Findings:The median number of tuberculosis notifications in the regions was 123.3 per 100?000 population (range: 54.5-265.7) in 2003, decreasing to 82.3 per 100?000 (range: 52.9-178.3) in 2016. We found large variations in the tuberculosis epidemiological profile across different regions. The principal coordinate analysis revealed that three aggregated indicators accounted for 55% of the variation. The first coordinate corresponded to tuberculosis prevalence and case notifications in the regions; the second to the severity of the disease among patients; and the third to the percentage of multidrug-resistant tuberculosis among tuberculosis patients. The regions where intervention was most urgently needed were Chukotka Autonomous Okrug, Jewish Autonomous Oblast and Tyva Republic. Conclusion:The variability in tuberculosis epidemiology across regions was likely due to differences in the quality of antituberculosis services. Precision in defining necessary interventions, as determined through the principal coordinate analysis approach, can guide focused tuberculosis control efforts.
Project description:BACKGROUND:The post-2015 End TB Strategy proposes targets of 50% reduction in tuberculosis incidence and 75% reduction in mortality from tuberculosis by 2025. We aimed to assess whether these targets are feasible in three high-burden countries with contrasting epidemiology and previous programmatic achievements. METHODS:11 independently developed mathematical models of tuberculosis transmission projected the epidemiological impact of currently available tuberculosis interventions for prevention, diagnosis, and treatment in China, India, and South Africa. Models were calibrated with data on tuberculosis incidence and mortality in 2012. Representatives from national tuberculosis programmes and the advocacy community provided distinct country-specific intervention scenarios, which included screening for symptoms, active case finding, and preventive therapy. FINDINGS:Aggressive scale-up of any single intervention scenario could not achieve the post-2015 End TB Strategy targets in any country. However, the models projected that, in the South Africa national tuberculosis programme scenario, a combination of continuous isoniazid preventive therapy for individuals on antiretroviral therapy, expanded facility-based screening for symptoms of tuberculosis at health centres, and improved tuberculosis care could achieve a 55% reduction in incidence (range 31-62%) and a 72% reduction in mortality (range 64-82%) compared with 2015 levels. For India, and particularly for China, full scale-up of all interventions in tuberculosis-programme performance fell short of the 2025 targets, despite preventing a cumulative 3·4 million cases. The advocacy scenarios illustrated the high impact of detecting and treating latent tuberculosis. INTERPRETATION:Major reductions in tuberculosis burden seem possible with current interventions. However, additional interventions, adapted to country-specific tuberculosis epidemiology and health systems, are needed to reach the post-2015 End TB Strategy targets at country level. FUNDING:Bill and Melinda Gates Foundation.