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Drug resistance diagnostics that rely on the detection of resistance-related mutations could expedite patient care and TB eradication. We perform minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole-genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We evaluate genome-wide associations between mutations in MTB genes or non-coding regions and resistance, followed by validation in an independent data set of 792 patient isolates. We confirm associations at 13 non-canonical loci, with two involving non-coding regions. Promoter mutations are measured to have smaller average effects on resistance than gene body mutations. We estimate the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causal loci, and emphasizes the contribution of the non-coding portion of the genome. Resistance to antibiotics hampers the treatment of infectious diseases such as tuberculosis (TB). Here, Farhat et al. perform genome-wide association testing for minimum inhibitory concentration (MIC) of 12 anti-TB drugs in whole-genome sequenced clinical M. tuberculosis isolates and identify 13 genomic loci.

ObjectivesHeteroresistant infections are defined as infections in which a mixture of drug-resistant and drug-susceptible populations are present. In Mycobacterium tuberculosis (M. tb), heteroresistance poses a challenge in diagnosis and has been linked with poor treatment outcomes. We compared the analytical sensitivity of molecular methods, such as GeneXpert and whole genome sequencing (WGS) in detecting heteroresistance when compared with the ‘gold standard’ phenotypic assay: the agar proportion method (APM).MethodsUsing two rounds of proficiency surveys with defined monoresistant BCG strains and mixtures of susceptible/resistant M. tb, we determined the limit of detection (LOD) of known resistance associated mutations.ResultsThe LOD for rifampin-R (RIF-R) detection was 1% using APM, 60% using GeneXpert MTB/RIF, 10% using GeneXpert MTB/RIF Ultra and 10% using WGS. While WGS could detect mutations beyond those associated with RIF resistance, the LOD for these other mutations was also 10%. Additionally, we observed instances where laboratories did not report resistance in the majority population, yet the mutations were present in the raw sequence data.ConclusionThe gold standard APM detects minority resistant populations at a lower proportion than molecular tests. Mycobacterium bovis BCG strains with defined resistance and extracted DNA from M. tb provided concordant results and can serve in quality control of laboratories offering molecular testing for resistance. Further research is required to determine whether the higher LOD of molecular tests is associated with negative treatment outcomes.

The wide geographic distribution of one clade of Mycobacterium tuberculosis, the Beijing genotype family, and its genetic homogeneity, suggests that strains belonging to this grouping might have a selective advantage over other M tuberculosis strains. This hypothesis was addressed by reviewing molecular-epidemiological, experimental, and clinical studies. Beijing strains represent about 50% of strains in east Asia and at least 13% of strains worldwide. Their emergence might be linked to escape from BCG vaccination, and to multidrug resistance, which is associated with the Beijing genotype in many areas. Different animal models have shown Beijing strains to be more virulent, and to cause more histopathological changes, higher outgrowth, and increased mortality. At a molecular level, Beijing strains have specific properties in terms of protein and lipid structures and their interaction with the human immune system. Finally, the Beijing genotype has been linked to polymorphisms in immune genes, suggesting the possibility of human–mycobacterial co-evolution. The emergence of the Beijing genotype family might represent an evolutionary response of M tuberculosis to vaccination or antibiotic treatment, with an important negative impact on tuberculosis control. More research is needed to further unravel the mechanisms underlying the emergence of M tuberculosis Beijing genotype strains, and examine the implications for future control strategies.

Patients with Mycobacterium tuberculosis isolates sharing identical DNA fingerprint patterns can be epidemiologically linked. However, municipal health services in the Netherlands are able to confirm an epidemiological link in only around 23% of the patients with isolates clustered by the conventional variable number of tandem repeat (VNTR) genotyping. This research aims to investigate whether whole genome sequencing (WGS) is a more reliable predictor of epidemiological links between tuberculosis patients than VNTR genotyping. VNTR genotyping and WGS were performed in parallel on all Mycobacterium tuberculosis complex isolates received at the Netherlands National Institute for Public Health and the Environment in 2016. Isolates were clustered by VNTR when they shared identical 24-loci VNTR patterns; isolates were assigned to a WGS cluster when the pair-wise genetic distance was ≤ 12 single nucleotide polymorphisms (SNPs). Cluster investigation was performed by municipal health services on all isolates clustered by VNTR in 2016. The proportion of epidemiological links identified among patients clustered by either method was calculated. In total, 535 isolates were genotyped, of which 25% (134/535) were clustered by VNTR and 14% (76/535) by WGS; the concordance between both typing methods was 86%. The proportion of epidemiological links among WGS clustered cases (57%) was twice as common than among VNTR clustered cases (31%). When WGS was applied, the number of clustered isolates was halved, while all epidemiologically linked cases remained clustered. WGS is therefore a more reliable tool to predict epidemiological links between tuberculosis cases than VNTR genotyping and will allow more efficient transmission tracing, as epidemiological investigations based on false clustering can be avoided.

The Global Project on Anti-Tuberculosis Drug Resistance has been gathering data since 1994. This study provides the latest data on the extent of drug resistance worldwide. Data for drug susceptibility were gathered from 90 726 patients in 83 countries and territories between 2002 and 2007. Standardised collection of results enabled comparison both between and within countries. Where possible, data for HIV status and resistance to second-line drugs were also obtained. Laboratory data were quality assured by the Supranational Tuberculosis Reference Laboratory Network. The median prevalence of resistance to any drug in new cases of tuberculosis was 11·1% (IQR 7·0–22·3). The prevalence of multidrug resistance in new tuberculosis cases ranged from 0% in eight countries to 7% in two provinces in China, 11·1% in Northern Mariana Islands (although reporting only two cases), and between 6·8% and 22·3% in nine countries of the former Soviet Union, including 19·4% in Moldova and 22·3% in Baku, Azerbaijan (median for countries surveyed 1·6%, IQR 0·6–3·9). Trend analysis showed that between 1994 and 2007, the prevalence of multidrug-resistant (MDR) tuberculosis in new cases increased substantially in South Korea and in Tomsk Oblast and Orel Oblast, Russia, but was stable in Estonia and Latvia. The prevalence of MDR tuberculosis in all tuberculosis cases decreased in Hong Kong and the USA. 37 countries and territories reported representative data on extensively drug-resistant (XDR) tuberculosis. Five countries, all from the former Soviet Union, reported 25 cases or more of XDR tuberculosis each, with prevalence among MDR-tuberculosis cases ranging between 6·6% and 23·7%. MDR tuberculosis remains a threat to tuberculosis control in provinces in China and countries of the former Soviet Union. Data on drug resistance are unavailable in many countries, especially in Africa, emphasising the need to develop easier methods for surveillance of resistance in tuberculosis. Global Project: United States Agency for International Development and Eli Lilly and Company. Drug resistance surveys: national tuberculosis programmes, the Government of the Netherlands, the Global Fund to Fight AIDS, Tuberculosis and Malaria, Japan International Cooperation Agency, and Kreditanstalt für Wiederaufbau.

Two billion people are infected with Mycobacterium tuberculosis , leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor , which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations.  Here we present a new tool, Mykrobe , which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at https://github.com/mykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates . Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rifampicin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) samples, and also show that Mykrobe gives concordant results with nanopore data.  We measure the ability of Mykrobe -based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools.

Africa is the second most populous continent and has perennial health challenges. Of the estimated 181 million school aged children in sub-Saharan Africa (SSA), nearly half suffer from ascariasis, trichuriasis, or a combination of these infections. Coupled with these is the problem of tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) infection, which is a leading cause of death in the region. Compared to the effect of the human immunodeficiency virus on the development of TB, the effect of chronic helminth infections is a neglected area of research, yet helminth infections are as ubiquitous as they are varied and may potentially have profound effects upon host immunity, particularly as it relates to TB infection, diagnosis, and vaccination. Protection against active TB is known to require a clearly delineated T-helper type 1 (Th1) response, while helminths induce a strong opposing Th2 and immune-regulatory host response. This Review highlights the potential challenges of helminth-TB co-infection in Africa and the need for further research.

Background Previous studies demonstrated that the diversity and composition of respiratory microbiota in TB patients were different from healthy individuals. Therefore, the aim of the present analysis was to estimate the relative proportion of respiratory microbiota at phylum and genus levels among TB cases and healthy controls. Methods The PubMed and Google Scholar online databases were searched to retrieve relevant studies for the analysis. The statistical analysis was done using STATA version 11, pooled estimates are presented using graphs. The summary of findings in included studies is also presented in Table 1. Results The phylum level analysis shows that the pooled proportions of Firmicutes , Proteobacteria , Bacteroidetes , Actinobacteria , and Crenarchaeota were determined among tuberculosis patients and healthy controls. In brief, Firmicutes , and Proteobacteria were the most abundant bacterial phyla in both TB cases and healthy controls, composing 39.9 and 22.7% in TB cases and 39.4 and 19.5% in healthy controls, respectively. The genus level analysis noted that Streptococcus (35.01%), Neisseria (27.1%), Prevotella (9.02%) and Veillonella (7.8%) were abundant in TB patients. The Prevotella (36.9%) , Gammaproteobacteria (22%), Streptococcus (19.2%) and Haemophilus (15.4%) were largely seen in healthy controls. Interestingly, Veillonella, Rothia , Leuconostoc were unique to TB cases, whereas Lactobacillus , and Gammaproteobacteria, Haemophilus, and Actinobacillus were identified only in healthy controls. Conclusion The composition of the respiratory microbiota in TB patients and healthy controls were quite different. More deep sequencing studies are needed to explore the microbial variation in the respiratory system in connection with TB.

The results of some reports have suggested that treatment of isoniazid-resistant tuberculosis with the recommended regimens of first-line drugs might be suboptimal. We updated a previous systematic review of treatment outcomes associated with use of first-line drugs in patients with tuberculosis resistant to isoniazid but not rifampicin. In this systematic review, we updated the results of a previous review to include randomised trials and cohort studies published in English, French, or Spanish to March 31, 2015, containing results of standardised treatment of patients with bacteriologically confirmed isoniazid-resistant tuberculosis (but not multidrug-resistant tuberculosis—ie, not resistant to rifampicin) in whom failure and relapse were bacteriologically confirmed. Results in patients with drug-sensitive tuberculosis included in the same studies were also analysed. We pooled treatment outcomes with random-effects meta-analysis. We identified 19 cohort studies and 33 trials with 3744 patients with isoniazid-resistant tuberculosis and 19 012 patients with drug-sensitive disease. The pooled rates of failure or relapse, or both, and acquired drug resistance with all drug regimens were 15% (95% CI 12–18) and 3·6% (2–5), respectively, in patients with isoniazid-resistant tuberculosis and 4% (3–5) and 0·6% (0·3–0·9) in those with drug-sensitive tuberculosis. Of patients with initial isoniazid-resistant tuberculosis with acquired drug resistance, 96% (93–99) had acquired multidrug-resistant disease. Treatment of isoniazid-resistant tuberculosis with the WHO standard regimen for new patients resulted in treatment failure, relapse, and acquired multidrug resistance in 11% (6–17), 10% (5–15) and 8% (3–13), respectively; treatment with the standard WHO regimen for previously treated patients resulted in treatment failure in 6% (2–10), relapse in 5% (2–8), and acquisition of multidrug resistance in 3% (0–6). For patients with drug-sensitive disease treated with the standard retreatment regimen the rates were 1% (0–2), 5% (4–7), and 0·3% (0–0·6). Treatment of isoniazid-resistant tuberculosis with first-line drugs resulted in suboptimal outcomes, supporting the need for better regimens. Standardised empirical treatment of new cases could be contributing substantially to the multidrug-resistant epidemic, particularly in settings where the prevalence of isoniazid resistance is high. Canadian Institutes of Health Research.