Emergence of multidrug-resistant Mycobacterium tuberculosis of the Beijing lineage in Portugal and Guinea-Bissau: a snapshot of moving clones by whole-genome sequencing.

The Beijing genotype comprises a highly disseminated strain type that is frequently associated with multidrug resistant (MDR) tuberculosis (TB) and increased transmissibility but, countries such as Portugal and Guinea-Bissau fall outside the regions phylogeographically associated with this specific genotype. Nevertheless, recent data shows that this genotype might be gradually emerging in these two countries as an underlying cause of primary MDR-TB. Here, we describe the emergence of Mycobacterium tuberculosis Beijing strains associated with MDR-TB in Portugal and Guinea-Bissau demonstrating the presence of the well described superclusters 100-32 and 94-32 in Portugal and Guinea-Bissau, respectively. Genome-wide analysis and comparison with a global genomic dataset of M. tuberculosis Beijing strains, revealed the presence of two genomic clusters encompassing isolates from Portugal and Guinea-Bissau, GC1 (n = 121) and GC2 (n = 39), both of which bore SNP signatures compatible with the 100-32/B0/W148 and 94-32/Central Asia Outbreak clades, respectively. Moreover, GC2 encompasses a cross-border cluster between Portugal, Guinea-Bissau and Brazil thus supporting migration-associated introduction of MDR-TB and subsequent clonal expansion at the community-level. The comparison with global Beijing datasets demonstrates the global reach of the disease and its complex dissemination across multiple countries while in parallel there are clear microevolutionary trajectories towards extensively drug resistant TB.

Author Correction: Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Machine Learning Predicts Accurately Mycobacterium tuberculosis Drug Resistance From Whole Genome Sequencing Data.

Background: Tuberculosis disease, caused by Mycobacterium tuberculosis, is a major public health problem. The emergence of M. tuberculosis strains resistant to existing treatments threatens to derail control efforts. Resistance is mainly conferred by mutations in genes coding for drug targets or converting enzymes, but our knowledge of these mutations is incomplete. Whole genome sequencing (WGS) is an increasingly common approach to rapidly characterize isolates and identify mutations predicting antimicrobial resistance and thereby providing a diagnostic tool to assist clinical decision making. Methods: We applied machine learning approaches to 16,688 M. tuberculosis isolates that have undergone WGS and laboratory drug-susceptibility testing (DST) across 14 antituberculosis drugs, with 22.5% of samples being multidrug resistant and 2.1% being extensively drug resistant. We used non-parametric classification-tree and gradient-boosted-tree models to predict drug resistance and uncover any associated novel putative mutations. We fitted separate models for each drug, with and without "co-occurrent resistance" markers known to be causing resistance to drugs other than the one of interest. Predictive performance was measured using sensitivity, specificity, and the area under the receiver operating characteristic curve, assuming DST results as the gold standard. Results: The predictive performance was highest for resistance to first-line drugs, amikacin, kanamycin, ciprofloxacin, moxifloxacin, and multidrug-resistant tuberculosis (area under the receiver operating characteristic curve above 96%), and lowest for third-line drugs such as D-cycloserine and Para-aminosalisylic acid (area under the curve below 85%). The inclusion of co-occurrent resistance markers led to improved performance for some drugs and superior results when compared to similar models in other large-scale studies, which had smaller sample sizes. Overall, the gradient-boosted-tree models performed better than the classification-tree models. The mutation-rank analysis detected no new single nucleotide polymorphisms linked to drug resistance. Discordance between DST and genotypically inferred resistance may be explained by DST errors, novel rare mutations, hetero-resistance, and nongenomic drivers such as efflux-pump upregulation. Conclusion: Our work demonstrates the utility of machine learning as a flexible approach to drug resistance prediction that is able to accommodate a much larger number of predictors and to summarize their predictive ability, thus assisting clinical decision making and single nucleotide polymorphism detection in an era of increasing WGS data generation.

Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs.

BACKGROUND: Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. RESULTS: We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93-95%) and 83% (95%CI 79-87%) with specificities of 98% (95%CI 98-99%) and 96% (95%CI 95-97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. CONCLUSIONS: The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings.

Spatial Network Mapping of Pulmonary Multidrug-Resistant Tuberculosis Cavities Using RNA Sequencing.

Rationale: There is poor understanding about protective immunity and the pathogenesis of cavitation in patients with tuberculosis.Objectives: To map pathophysiological pathways at anatomically distinct positions within the human tuberculosis cavity.Methods: Biopsies were obtained from eight predetermined locations within lung cavities of patients with multidrug-resistant tuberculosis undergoing therapeutic surgical resection (n = 14) and healthy lung tissue from control subjects without tuberculosis (n = 10). RNA sequencing, immunohistochemistry, and bacterial load determination were performed at each cavity position. Differentially expressed genes were normalized to control subjects without tuberculosis, and ontologically mapped to identify a spatially compartmentalized pathophysiological map of the cavity. In silico perturbation using a novel distance-dependent dynamical sink model was used to investigate interactions between immune networks and bacterial burden, and to integrate these identified pathways.Measurements and Main Results: The median (range) lung cavity volume on positron emission tomography/computed tomography scans was 50 cm3 (15-389 cm3). RNA sequence reads (31% splice variants) mapped to 19,049 annotated human genes. Multiple proinflammatory pathways were upregulated in the cavity wall, whereas a downregulation "sink" in the central caseum-fluid interface characterized 53% of pathways including neuroendocrine signaling, calcium signaling, triggering receptor expressed on myeloid cells-1, reactive oxygen and nitrogen species production, retinoic acid-mediated apoptosis, and RIG-I-like receptor signaling. The mathematical model demonstrated that neuroendocrine, protein kinase C-θ, and triggering receptor expressed on myeloid cells-1 pathways, and macrophage and neutrophil numbers, had the highest correlation with bacterial burden (r > 0.6), whereas T-helper effector systems did not.Conclusions: These data provide novel insights into host immunity to Mycobacterium tuberculosis-related cavitation. The pathways defined may serve as useful targets for the design of host-directed therapies, and transmission prevention interventions.

Clonal expansion across the seas as seen through CPLP-TB database: A joint effort in cataloguing Mycobacterium tuberculosis genetic diversity in Portuguese-speaking countries.

Tuberculosis (TB) remains a major health problem within the Community of Portuguese Language Speaking Countries (CPLP). Despite the marked variation in TB incidence across its member-states and continued human migratory flux between countries, a considerable gap in the knowledge on the Mycobacterium tuberculosis population structure and strain circulation between the countries still exists. To address this, we have assembled and analysed the largest CPLP M. tuberculosis molecular and drug susceptibility dataset, comprised by a total of 1447 clinical isolates, including 423 multidrug-resistant isolates, from five CPLP countries. The data herein presented reinforces Latin American and Mediterranean (LAM) strains as the hallmark of M. tuberculosis populational structure in the CPLP coupled with country-specific differential prevalence of minor clades. Moreover, using high-resolution typing by 24-loci MIRU-VNTR, six cross-border genetic clusters were detected, thus supporting recent clonal expansion across the Lusophone space. To make this data available to the scientific community and public health authorities we developed CPLP-TB (available at http://cplp-tb.ff.ulisboa.pt), an online database coupled with web-based tools for exploratory data analysis. As a public health tool, it is expected to contribute to improved knowledge on the M. tuberculosis population structure and strain circulation within the CPLP, thus supporting the risk assessment of strain-specific trends.

Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase.

Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibility testing (DST) and clinical data. We developed a unified analysis variant pipeline (UVP) ( https://github.com/CPTR-ReSeqTB/UVP ) to identify variants and assign lineage from MTBC sequence data. Stringent thresholds and quality control measures were incorporated in this open source tool. The pipeline was validated using a well-characterized dataset of 90 diverse MTBC isolates with conventional DST and DNA Sanger sequencing data. The UVP exhibited 98.9% agreement with the variants identified using Sanger sequencing and was 100% concordant with conventional methods of assigning lineage. We analyzed 4636 publicly available MTBC isolates in the ReSeqTB platform representing all seven major MTBC lineages. The variants detected have an above 94% accuracy of predicting drug based on the accompanying DST results in the platform. The aggregation of variants over time in the platform will establish confidence-graded mutations statistically associated with phenotypic drug resistance. These tools serve as critical reference standards for future molecular diagnostic assay developers, researchers, public health agencies and clinicians working towards the control of drug-resistant tuberculosis.

Identifying mixed Mycobacterium tuberculosis infections from whole genome sequence data.

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.

Use of whole genome sequencing in surveillance of drug resistant tuberculosis.

INTRODUCTION: The threat of resistance to anti-tuberculosis drugs is of global concern. Current efforts to monitor resistance rely on phenotypic testing where cultured bacteria are exposed to critical concentrations of the drugs. Capacity for such testing is low in TB endemic countries. Drug resistance is caused by mutations in the Mycobacterium tuberculosis genome and whole genome sequencing to detect these mutations offers an alternative means of assessing resistance. Areas covered: The challenges of assessing TB drug resistance are discussed. Progress in elucidating the M. tuberculosis resistome and evidence of the accuracy of next generation sequencing for detecting resistance is reviewed. Expert Commentary: There are considerable advantages to using next generation sequencing for TB drug resistance surveillance. Accuracy is high for detecting resistance to the major first-line drugs but is currently lower for the second-line drugs due to our incomplete knowledge regarding resistance causing mutations. With the advances in sequencing technology and the opportunity to replace phenotypic drug susceptibility testing with safer and more cost effective methods it would appear that the question is when to implement. Current bottlenecks are sample extraction to allow whole genome sequencing directly from sputum and the lack of bioinformatics expertise in some TB endemic countries.

Author Correction: Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis.

In the version of this article initially published, the URL listed for TubercuList was incorrect. The correct URL is https://mycobrowser.epfl.ch/. The error has been corrected in the HTML and PDF versions of the article.

Tuberculosis: advances and challenges in development of new diagnostics and biomarkers.

Tuberculosis remains the leading cause of death from an infectious disease worldwide. Early and accurate diagnosis and detection of drug-sensitive and drug-resistant tuberculosis is essential for achieving global tuberculosis control. Despite the introduction of the Xpert MTB/RIF assay as the first-line rapid tuberculosis diagnostic test, the gap between global estimates of incidence and new case notifications is 4·1 million people. More accurate, rapid, and cost-effective screening tests are needed to improve case detection. Diagnosis of extrapulmonary tuberculosis and tuberculosis in children, people living with HIV, and pregnant women remains particularly problematic. The diagnostic molecular technology landscape has continued to expand, including the development of tests for resistance to several antituberculosis drugs. Biomarkers are urgently needed to indicate progression from latent infection to clinical disease, to predict risk of reactivation after cure, and to provide accurate endpoints for drug and vaccine trials. Sophisticated bioinformatic computational tools and systems biology approaches are being applied to the discovery and validation of biomarkers, with substantial progress taking place. New data have been generated from the study of T-cell responses and T-cell function, serological studies, flow cytometric-based assays, and protein and gene expression studies. Alternative diagnostic strategies under investigation as potential screening and triaging tools include non-sputum-based detection with breath-based tests and automated digital radiography. We review developments and key achievements in the search for new tuberculosis diagnostics and biomarkers. We highlight gaps and challenges in evaluation and rollout of new diagnostics and biomarkers, and prioritise areas needing further investment, including impact assessment and cost-benefit studies.

Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis.

To characterize the genetic determinants of resistance to antituberculosis drugs, we performed a genome-wide association study (GWAS) of 6,465 Mycobacterium tuberculosis clinical isolates from more than 30 countries. A GWAS approach within a mixed-regression framework was followed by a phylogenetics-based test for independent mutations. In addition to mutations in established and recently described resistance-associated genes, novel mutations were discovered for resistance to cycloserine, ethionamide and para-aminosalicylic acid. The capacity to detect mutations associated with resistance to ethionamide, pyrazinamide, capreomycin, cycloserine and para-aminosalicylic acid was enhanced by inclusion of insertions and deletions. Odds ratios for mutations within candidate genes were found to reflect levels of resistance. New epistatic relationships between candidate drug-resistance-associated genes were identified. Findings also suggest the involvement of efflux pumps (drrA and Rv2688c) in the emergence of resistance. This study will inform the design of new diagnostic tests and expedite the investigation of resistance and compensatory epistatic mechanisms.

Methylation in Mycobacterium tuberculosis is lineage specific with associated mutations present globally.

DNA methylation is an epigenetic modification of the genome involved in regulating crucial cellular processes, including transcription and chromosome stability. Advances in PacBio sequencing technologies can be used to robustly reveal methylation sites. The methylome of the Mycobacterium tuberculosis complex is poorly understood but may be involved in virulence, hypoxic survival and the emergence of drug resistance. In the most extensive study to date, we characterise the methylome across the 4 major lineages of M. tuberculosis and 2 lineages of M. africanum, the leading causes of tuberculosis disease in humans. We reveal lineage-specific methylated motifs and strain-specific mutations that are abundant globally and likely to explain loss of function in the respective methyltransferases. Our work provides a set of sixteen new complete reference genomes for the Mycobacterium tuberculosis complex, including complete lineage 5 genomes. Insights into lineage-specific methylomes will further elucidate underlying biological mechanisms and other important phenotypes of the epi-genome.

A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis.

A clear understanding of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.We identified 286 confidence-graded mutations associated with resistance. Compared to phenotypic methods, sensitivity (95% CI) for rifampicin was 90.3% (89.6-90.9%), while for isoniazid it was 78.2% (77.4-79.0%) and their specificities were 96.3% (95.7-96.8%) and 94.4% (93.1-95.5%), respectively. For second-line drugs, sensitivity varied from 67.4% (64.1-70.6%) for capreomycin to 88.2% (85.1-90.9%) for moxifloxacin, with specificity ranging from 90.0% (87.1-92.5%) for moxifloxacin to 99.5% (99.0-99.8%) for amikacin.This study provides a standardised and comprehensive approach for the interpretation of mutations as predictors of M. tuberculosis drug-resistant phenotypes. These data have implications for the clinical interpretation of molecular diagnostics and next-generation sequencing as well as efficient individualised therapy for patients with drug-resistant tuberculosis.

A multiple genome analysis of Mycobacterium tuberculosis reveals specific novel genes and mutations associated with pyrazinamide resistance.

BACKGROUND: Tuberculosis (TB) is a major global health problem and drug resistance compromises the efforts to control this disease. Pyrazinamide (PZA) is an important drug used in both first and second line treatment regimes. However, its complete mechanism of action and resistance remains unclear. RESULTS: We genotyped and sequenced the complete genomes of 68 M. tuberculosis strains isolated from unrelated TB patients in Peru. No clustering pattern of the strains was verified based on spoligotyping. We analyzed the association between PZA resistance with non-synonymous mutations and specific genes. We found mutations in pncA and novel genes significantly associated with PZA resistance in strains without pncA mutations. These included genes related to transportation of metal ions, pH regulation and immune system evasion. CONCLUSIONS: These results suggest potential alternate mechanisms of PZA resistance that have not been found in other populations, supporting that the antibacterial activity of PZA may hit multiple targets.

Single nucleotide polymorphisms in efflux pumps genes in extensively drug resistant Mycobacterium tuberculosis isolates from Pakistan.

It is challenging to understand mechanisms of drug resistance in Mycobacterium tuberculosis (MTB) due to the large variability in resistance associated genes. Efflux pump genes contribute to drug resistance and thus add to this complexity. Efflux pump gene protein superfamilies have been characterized by genome analysis of drug resistant strains and through in vitro transcriptional studies. However, there is limited information regarding efflux pump genes in extensively drug resistant (XDR) tuberculosis (TB) isolates. Whole genome sequencing (WGS) based analysis of 37 extensively drug resistant (XDR) and five drug sensitive (DS) MTB clinical isolates was performed. Single nucleotide polymorphisms (SNPs) in efflux pump genes Rv0194, Rv1217, Rv1218, drrA, drrB, Rv1258, Rv1634, Rv2688, Rv1273, Rv1819, Rv1458, Rv1877 and Rv1250 were determined in the clinical isolates as compared with the H37Rv reference strain. Allele frequencies of SNPs identified in XDR strains were compared with DS strains. Gene expression of Rv0194, Rv2688, Rv1634, drrA and drrB was determined in XDR -TB isolates (n = 9), DS-TB strains (n = 4) and H37Rv. We identified SNPs in XDR-TB isolates which were either unique or present at very low frequencies in DS strains; Rv0194 G170V; Rv1217 L151R; Rv1258 P369T and G391R; Rv1273 S118G and I175T; Rv1877 I534T; Rv1250 V318X/A and S333A, and Rv2688 P156T. The expression of Rv2688 and drrB was found to be raised in XDR-TB as compared with DS-TB strains. We identified unique SNPs in efflux pump genes which may be associated with increased drug resistance in the isolates. Increased levels of Rv2688 and drrB efflux pump gene expression observed in XDR strains even in the absence of antibiotics suggests that these clinical isolates may be more refractory to treatment. Further studies are required to directly associate these mutations with increased resistance in MTB.

The epidemiology, pathogenesis, transmission, diagnosis, and management of multidrug-resistant, extensively drug-resistant, and incurable tuberculosis.

Global tuberculosis incidence has declined marginally over the past decade, and tuberculosis remains out of control in several parts of the world including Africa and Asia. Although tuberculosis control has been effective in some regions of the world, these gains are threatened by the increasing burden of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis. XDR tuberculosis has evolved in several tuberculosis-endemic countries to drug-incurable or programmatically incurable tuberculosis (totally drug-resistant tuberculosis). This poses several challenges similar to those encountered in the pre-chemotherapy era, including the inability to cure tuberculosis, high mortality, and the need for alternative methods to prevent disease transmission. This phenomenon mirrors the worldwide increase in antimicrobial resistance and the emergence of other MDR pathogens, such as malaria, HIV, and Gram-negative bacteria. MDR and XDR tuberculosis are associated with high morbidity and substantial mortality, are a threat to health-care workers, prohibitively expensive to treat, and are therefore a serious public health problem. In this Commission, we examine several aspects of drug-resistant tuberculosis. The traditional view that acquired resistance to antituberculous drugs is driven by poor compliance and programmatic failure is now being questioned, and several lines of evidence suggest that alternative mechanisms-including pharmacokinetic variability, induction of efflux pumps that transport the drug out of cells, and suboptimal drug penetration into tuberculosis lesions-are likely crucial to the pathogenesis of drug-resistant tuberculosis. These factors have implications for the design of new interventions, drug delivery and dosing mechanisms, and public health policy. We discuss epidemiology and transmission dynamics, including new insights into the fundamental biology of transmission, and we review the utility of newer diagnostic tools, including molecular tests and next-generation whole-genome sequencing, and their potential for clinical effectiveness. Relevant research priorities are highlighted, including optimal medical and surgical management, the role of newer and repurposed drugs (including bedaquiline, delamanid, and linezolid), pharmacokinetic and pharmacodynamic considerations, preventive strategies (such as prophylaxis in MDR and XDR contacts), palliative and patient-orientated care aspects, and medicolegal and ethical issues.

Outcomes, infectiousness, and transmission dynamics of patients with extensively drug-resistant tuberculosis and home-discharged patients with programmatically incurable tuberculosis: a prospective cohort study.

BACKGROUND: The emergence of programmatically incurable tuberculosis threatens to destabilise control efforts. The aim of this study was to collect prospective patient-level data to inform treatment and containment strategies. METHODS: In a prospective cohort study, 273 South African patients with extensively drug-resistant tuberculosis, or resistance beyond extensively drug-resistant tuberculosis, were followed up over a period of 6 years. Transmission dynamics, infectiousness, and drug susceptibility were analysed in a subset of patients from the Western Cape using whole-genome sequencing (WGS; n=149), a cough aerosol sampling system (CASS; n=26), and phenotypic testing for 18 drugs (n=179). FINDINGS: Between Oct 1, 2008, and Oct 31, 2012, we enrolled and followed up 273 patients for a median of 20·3 months (IQR 9·6-27·8). 203 (74%) had programmatically incurable tuberculosis and unfavourable outcomes (treatment failure, relapse, default, or death despite treatment with a regimen based on capreomycin, aminosalicylic acid, or both). 172 (63%) patients were discharged home, of whom 104 (60%) had an unfavourable outcome. 54 (31%) home-discharged patients had failed treatment, with a median time to death after discharge of 9·9 months (IQR 4·2-17·4). 35 (20%) home-discharged cases were smear-positive at discharge. Using CASS, six (23%) of 26 home-discharged cases with data available expectorated infectious culture-positive cough aerosols in the respirable range (<5 µm), and most reported inter-person contact with suboptimal protective mask usage. WGS identified 17 (19%) of the 90 patients (with available sequence data) that were discharged home before the diagnosis of 20 downstream cases of extensively drug-resistant tuberculosis with almost identical sequencing profiles suggestive of community-based transmission (five or fewer single nucleotide polymorphisms different and with identical resistance-encoding mutations for 14 drugs). 11 (55%) of these downstream cases had HIV co-infection and ten (50%) had died by the end of the study. 22 (56%) of 39 isolates in patients discharged home after treatment failure were resistant to eight or more drugs. However, five (16%) of 31 isolates were susceptible to rifabutin and more than 90% were likely to be sensitive to linezolid, bedaquiline, and delamanid. INTERPRETATION: More than half of the patients with programmatically incurable tuberculosis were discharged into the community where they remained for an average of 16 months, were at risk of expectorating infectious cough aerosols, and posed a threat of transmission of extensively drug-resistant tuberculosis. Urgent action, including appropriate containment strategies, is needed to address this situation. Access to delamanid, bedaquiline, linezolid, and rifabutin, when appropriate, must be accelerated along with comprehensive drug susceptibility testing. FUNDING: UK Medical Research Council, South African Medical Research Council, South African National Research Foundation, European & Developing Countries Clinical Trials Partnership, Oppenheimer Foundation, Newton Fund, Biotechnology and Biological Sciences Research Council, King Abdullah University of Science & Technology.

Effect of new tuberculosis diagnostic technologies on community-based intensified case finding: a multicentre randomised controlled trial.

BACKGROUND: Inadequate case detection results in high levels of undiagnosed tuberculosis in sub-Saharan Africa. Data for the effect of new diagnostic tools when used for community-based intensified case finding are not available, so we investigated whether the use of sputum Xpert-MTB/RIF and the Determine TB LAM urine test in two African communities could be effective. METHODS: In a pragmatic, randomised, parallel-group trial with individual randomisation stratified by country, we compared sputum Xpert-MTB/RIF, and if HIV-infected, the Determine TB LAM urine test (novel diagnostic group), with laboratory-based sputum smear microscopy (routine diagnostic group) for intensified case finding in communities with high tuberculosis and HIV prevalence in Cape Town, South Africa, and Harare, Zimbabwe. Participants were randomly assigned (1:1) to these groups with computer-generated allocation lists, using culture as the reference standard. In Cape Town, participants were randomised and tested at an Xpert-equipped mobile van, while in Harare, participants were driven to a local clinic where the same diagnostic tests were done. The primary endpoint was the proportion of culture-positive tuberculosis cases initiating tuberculosis treatment in each study group at 60 days. This trial is registered at ClinicalTrials.gov, number NCT01990274. FINDINGS: Between Oct 18, 2013, and March 31, 2015, 2261 individuals were screened and 875 (39%) of these met the criteria for diagnostic testing. 439 participants were randomly assigned to the novel group and 436 to the routine group. 74 (9%) of 875 participants had confirmed tuberculosis. If late culture-based treatment initiation was excluded, more patients with culture-positive tuberculosis were initiated on treatment in the novel group at 60 days (36 [86%] of 42 in the novel group vs 18 [56%] of 32 in the routine group). Thus the difference in the proportion initiating treatment between groups was 29% (95% CI 9-50, p=0·0047) and 53% more patients initiated therapy in the novel diagnostic group than in the routine diagnostic group. One culture-positive patient was treated based only on a positive LAM test. INTERPRETATION: Compared with traditional tools, Xpert-MTB/RIF for community-based intensified case finding in HIV and tuberculosis-endemic settings increased the proportion of patients initiating treatment. By contrast, urine LAM testing was not found to be useful for intensive case finding in this setting. FUNDING: European and Developing Countries Clinical Trials Partnership and South African Medical Research Council.

Removing the bottleneck in whole genome sequencing of Mycobacterium tuberculosis for rapid drug resistance analysis: a call to action.

Whole genome sequencing (WGS) can provide a comprehensive analysis of Mycobacterium tuberculosis mutations that cause resistance to anti-tuberculosis drugs. With the deployment of bench-top sequencers and rapid analytical software, WGS is poised to become a useful tool to guide treatment. However, direct sequencing from clinical specimens to provide a full drug resistance profile remains a serious challenge. This article reviews current practices for extracting M. tuberculosis DNA and possible solutions for sampling sputum. Techniques under consideration include enzymatic digestion, physical disruption, chemical degradation, detergent solubilization, solvent extraction, ligand-coated magnetic beads, silica columns, and oligonucleotide pull-down baits. Selective amplification of genomic bacterial DNA in sputum prior to WGS may provide a solution, and differential lysis to reduce the levels of contaminating human DNA is also being explored. To remove this bottleneck and accelerate access to WGS for patients with suspected drug-resistant tuberculosis, it is suggested that a coordinated and collaborative approach be taken to more rapidly optimize, compare, and validate methodologies for sequencing from patient samples.