Tuberculosis caused 20% of all human deaths in the Western world between the 17th and 19th centuries, and remains a cause of high mortality in developing countries. In analogy to other crowd diseases, the origin of human tuberculosis has been associated with the Neolithic Demographic Transition, but recent studies point to a much earlier origin. Here we used 259 whole-genome sequences to reconstruct the evolutionary history of the Mycobacterium tuberculosis complex (MTBC). Coalescent analyses indicate that MTBC emerged about 70 thousand years ago, accompanied migrations of anatomically modern humans out of Africa, and expanded as a consequence of increases in human population density during the Neolithic. This long co-evolutionary history is consistent with MTBC displaying characteristics indicative of adaptation to both low- and high host densities.

Background: The Direct Repeat locus of the Mycobacterium tuberculosis complex (MTC) is a member of the CRISPR (Clustered regularly interspaced short palindromic repeats) sequences family. Spoligotyping is the widely used PCR-based reverse-hybridization blotting technique that assays the genetic diversity of this locus and is useful both for clinical laboratory, molecular epidemiology, evolutionary and population genetics. It is easy, robust, cheap, and produces highly diverse portable numerical results, as the result of the combination of (1) Unique Events Polymorphism (UEP) (2) Insertion-Sequence-mediated genetic recombination. Genetic convergence, although rare, was also previously demonstrated. Three previous international spoligotype databases had partly revealed the global and local geographical structures of MTC bacilli populations, however, there was a need for the release of a new, more representative and extended, international spoligotyping database.

SummaryBackgroundDiagnosing drug-resistance remains an obstacle to the elimination of tuberculosis. Phenotypic drug-susceptibility testing is slow and expensive, and commercial genotypic assays screen only common resistance-determining mutations. We used whole-genome sequencing to characterise common and rare mutations predicting drug resistance, or consistency with susceptibility, for all first-line and second-line drugs for tuberculosis.MethodsBetween Sept 1, 2010, and Dec 1, 2013, we sequenced a training set of 2099 Mycobacterium tuberculosis genomes. For 23 candidate genes identified from the drug-resistance scientific literature, we algorithmically characterised genetic mutations as not conferring resistance (benign), resistance determinants, or uncharacterised. We then assessed the ability of these characterisations to predict phenotypic drug-susceptibility testing for an independent validation set of 1552 genomes. We sought mutations under similar selection pressure to those characterised as resistance determinants outside candidate genes to account for residual phenotypic resistance.FindingsWe characterised 120 training-set mutations as resistance determining, and 772 as benign. With these mutations, we could predict 89·2% of the validation-set phenotypes with a mean 92·3% sensitivity (95% CI 90·7–93·7) and 98·4% specificity (98·1–98·7). 10·8% of validation-set phenotypes could not be predicted because uncharacterised mutations were present. With an in-silico comparison, characterised resistance determinants had higher sensitivity than the mutations from three line-probe assays (85·1% vs 81·6%). No additional resistance determinants were identified among mutations under selection pressure in non-candidate genes.InterpretationA broad catalogue of genetic mutations enable data from whole-genome sequencing to be used clinically to predict drug resistance, drug susceptibility, or to identify drug phenotypes that cannot yet be genetically predicted. This approach could be integrated into routine diagnostic workflows, phasing out phenotypic drug-susceptibility testing while reporting drug resistance early.

This paper describes an action framework for countries with low tuberculosis (TB) incidence (<100 TB cases per million population) that are striving for TB elimination. The framework sets out priority interventions required for these countries to progress first towards “pre-elimination” (<10 cases per million) and eventually the elimination of TB as a public health problem (less than one case per million). TB epidemiology in most low-incidence countries is characterised by a low rate of transmission in the general population, occasional outbreaks, a majority of TB cases generated from progression of latent TB infection (LTBI) rather than local transmission, concentration to certain vulnerable and hard-to-reach risk groups, and challenges posed by cross-border migration. Common health system challenges are that political commitment, funding, clinical expertise and general awareness of TB diminishes as TB incidence falls. The framework presents a tailored response to these challenges, grouped into eight priority action areas: 1) ensure political commitment, funding and stewardship for planning and essential services; 2) address the most vulnerable and hard-to-reach groups; 3) address special needs of migrants and cross-border issues; 4) undertake screening for active TB and LTBI in TB contacts and selected high-risk groups, and provide appropriate treatment; 5) optimise the prevention and care of drug-resistant TB; 6) ensure continued surveillance, programme monitoring and evaluation and case-based data management; 7) invest in research and new tools; and 8) support global TB prevention, care and control. The overall approach needs to be multisectorial, focusing on equitable access to high-quality diagnosis and care, and on addressing the social determinants of TB. Because of increasing globalisation and population mobility, the response needs to have both national and global dimensions.

Mycobacterium tuberculosis strains of the Beijing lineage are globally distributed and are associated with the massive spread of multidrug-resistant (MDR) tuberculosis in Eurasia. Here we reconstructed the biogeographical structure and evolutionary history of this lineage by genetic analysis of 4,987 isolates from 99 countries and whole-genome sequencing of 110 representative isolates. We show that this lineage initially originated in the Far East, from where it radiated worldwide in several waves. We detected successive increases in population size for this pathogen over the last 200 years, practically coinciding with the Industrial Revolution, the First World War and HIV epidemics. Two MDR clones of this lineage started to spread throughout central Asia and Russia concomitantly with the collapse of the public health system in the former Soviet Union. Mutations identified in genes putatively under positive selection and associated with virulence might have favored the expansion of the most successful branches of the lineage.

Tuberculosis control relies on the identification and preventive treatment of individuals who are latently infected with Mycobacterium tuberculosis. However, direct identification of latent tuberculosis infection is not possible. The diagnostic tests used to identify individuals latently infected with M. tuberculosis, the in vivo tuberculin skin test and the ex vivo interferon-c release assays (IGRAs), are designed to identify an adaptive immune response against, but not necessarily a latent infection with, M. tuberculosis. The proportion of individuals who truly remain infected with M. tuberculosis after tuberculin skin test or IGRA conversion is unknown. It is also uncertain how long adaptive immune responses towards mycobacterial antigens persist in the absence of live mycobacteria. Clinical management and public healthcare policies for preventive chemotherapy against tuberculosis could be improved, if we were to gain a better understanding on M. tuberculosis latency and reactivation. This statement by the TBNET summarises knowledge and limitations of the currently available tests used in adults and children for the diagnosis of latent tuberculosis infection.In summary, the main issue regarding testing is to restrict it to those who are known to be at higher risk of developing tuberculosis and who are willing to accept preventive chemotherapy.

The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.

In an outbreak investigation of Mycobacterium tuberculosis comparing whole genome sequencing (WGS) with traditional genotyping, Stefan Niemann and colleagues found that classical genotyping falsely clustered some strains, and WGS better reflected contact tracing.