Einleitung: Beschreibung vorläufiger Ergebnisse der initialen Tuberkulosebehandlung, Diagnoseverzögerung und Medikamentenresistenz aus 6 Studienregionen. Methodik: Zwischen 10/2001 und 3/2004 wurden epidemiologische Patientendaten (2562 Fälle) vom DZK in Zusammenarbeit mit 4 Laboratorien und regionalen Gesundheitsämtern gesammelt und ausgewertet. Ergebnisse: Der Zeitraum zwischen erstem Arztbesuch und Diagnosestellung lag durchschnittlich bei 53 Tagen (Median 22; 95 KI: 47/59; n=1806). Der Zeitraum zwischen Tuberkuloseverdacht und Diagnose betrug bei 55,4% der Patienten bis zu 10 Tage. Bei 26,8% dauerte die Diagnosestellung 11–30 Tage, bei 11,6% 1–2 Monate und bei 6,2% kam es zu einer Verzögerung von über zwei Monaten (Mittelwert 24, Median 8, 95% KI: 18/30 Tage; n=2225). Die medizinische Betreuung der Patienten erfolgte bei 83,6% (n=2127) teilweise stationär. 64,5% wurden zu irgendeinem Behandlungszeitpunkt auch durch ihren Hausarzt, 62,6% durch einen Lungenfacharzt betreut. Die durchschnittliche Liegedauer im Krankenhaus betrug 52,5 Tage (Median 36, 95% KI: 50/55; n=2116). 68,6% der im Verlauf bestätigten kulturell bestätigten Patienten wurden initial mit 4 oder 5 Antituberkulotika behandelt, 29,4% mit 3 Medikamenten. 84,7% erhielten eine Medikamentenkombination, die H, R und Z enthielt. Initial wird eine große Anzahl verschiedener Therapieregime eingesetzt. Jegliche Resistenz gegen eines der Erstrangmedikamente (HRESZ) trat bei 12,2% der Patienten auf, und Multiresistenz (MDR) bei 1,2%. Schlussfolgerung: Die TB-Diagnose wird häufig erst spät gestellt und die nationalen Therapierichtlinien werden nicht ausreichend befolgt. Die große Mehrzahl der Tuberkulosepatienten in Deutschland wird während der Behandlung zeitweilig stationär betreut. Resistenzen treten öfter bei im Ausland geborenen und vorbehandelten Patienten auf. Es besteht dringender Bedarf an kontinuierlicher Aus- und Weiterbildung.
ABSTRACT This paper presents an update on the content, accessibility and analytical tools of the EnteroBase platform for web-based pathogen genome analysis. EnteroBase provides manually curated databases of genome sequence data and associated metadata from currently >1.1 million bacterial isolates, more recently including Streptococcus spp. and Mycobacterium tuberculosis . We have implemented the genome-based detection of antimicrobial resistance determinants and the new bubble plot graphical tool for visualising bacterial genomic population structures, based on pre-computed hierarchical clusters. Access to data and analysis tools is provided through an enhanced graphical user interface and a new application programming interface (RESTful API). EnteroBase is now being developed and operated by an international consortium, to accelerate the development of the platform and ensure the longevity of the resources built. EnteroBase can be accessed at https://enterobase.warwick.ac.uk as well as https://enterobase.dsmz.de . GRAPHICAL ABSTRACT
Tuberculosis exerts a tremendous burden on global health, with ∼9 million new infections and ∼2 million deaths annually. The Mycobacterium tuberculosis complex (MTC) was initially regarded as a highly homogeneous population; however, recent data suggest the causative agents of tuberculosis are more genetically and functionally diverse than appreciated previously. The impact of this natural variation on the virulence and clinical manifestations of the pathogen remains largely unknown. This report examines the effect of genetic diversity among MTC clinical isolates on global gene expression and survival within macrophages. We discovered lineage-specific transcription patterns in vitro and distinct intracellular growth profiles associated with specific responses to host-derived environmental cues. Strain comparisons also facilitated delineation of a core intracellular transcriptome, including genes with highly conserved regulation across the global panel of clinical isolates. This study affords new insights into the genetic information that M. tuberculosis has conserved under selective pressure during its long-term interactions with its human host.
Antibiotic resistance among bacterial pathogens poses a major global health threat. Mycobacterium tuberculosis complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the low growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug susceptibility testing (DST) for this pathogen is to rely on genotypic techniques.
Ethambutol (EMB) is a major component of the first-line therapy of tuberculosis. Mutations in codon 306 of embB (embB306) were suggested as a major resistance mechanism in clinical isolates. To directly analyze the impact of individual embB306 mutations on EMB resistance, we used allelic exchange experiments to generate embB306 mutants of M. tuberculosis H37Rv. The level of EMB resistance conferred by particular mutations was measured in vitro and in vivo after EMB therapy by daily gavage in a mouse model of aerogenic tuberculosis. The wild-type embB306 ATG codon was replaced by embB306 ATC, ATA, or GTG, respectively. All of the obtained embB306 mutants exhibited a 2- to 4-fold increase in EMB MIC compared to the wild-type H37Rv. In vivo, the one selected embB306 GTG mutant required a higher dose of ethambutol to restrict its growth in the lung compared to wild-type H37Rv. These experiments demonstrate that embB306 point mutations enhance the EMB MIC in vitro to a moderate, but significant extent, and reduce the efficacy of EMB treatment in the animal model. We propose that conventional EMB susceptibility testing, in combination with embB306 genotyping, may guide dose adjustment to avoid clinical treatment failure in these low-level resistant strains.
Nine Kazakhstan oblasts, 2001.To analyse the genetic relationship of drug-resistant Mycobacterium tuberculosis strains from Kazakhstan and to determine the frequency of the Beijing genotype.All drug-resistant smear-positive cases identified in nine oblasts during the 2001 nationwide drug resistance survey were analysed by IS6110 fingerprinting and spoligotyping. Isolates were obtained from 150 patients (64 new and 86 retreated cases).Eight cases (5.3%) of dual infection were identified. Of the remaining 142 strains, 91 (64.1%) were grouped in 18 clusters, indicating a high rate of recent transmission of resistant tuberculosis (TB). This was further confirmed by the origin of the patients as well as by the similar drug resistance patterns of the clustered strains. Accordingly, more than one third of all clustered strains were new cases. About 70% of the resistant strains belonged to the Beijing genotype, compared to only 37.5% in a control group of 40 susceptible isolates.Transmission of drug-resistant strains seems to contribute to the spread of resistant TB in this high incidence region. The Beijing genotype should be seen as a major cause of drug-resistant TB in Kazakhstan and was found to be associated with drug resistance.
Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages.We used a large cohort of TB patients from 16 countries across six continents where whole-genome sequences for each isolate and associated phenotype to anti-TB drugs were obtained using drug susceptibility testing recommended by the World Health Organization. We then proposed an end-to-end multi-task model with deep denoising auto-encoder (DeepAMR) for multiple drug classification and developed DeepAMR_cluster, a clustering variant based on DeepAMR, for learning clusters in latent space of the data. The results showed that DeepAMR outperformed baseline model and four machine learning models with mean AUROC from 94.4% to 98.7% for predicting resistance to four first-line drugs [i.e. isoniazid (INH), ethambutol (EMB), rifampicin (RIF), pyrazinamide (PZA)], multi-drug resistant TB (MDR-TB) and pan-susceptible TB (PANS-TB: MTB that is susceptible to all four first-line anti-TB drugs). In the case of INH, EMB, PZA and MDR-TB, DeepAMR achieved its best mean sensitivity of 94.3%, 91.5%, 87.3% and 96.3%, respectively. While in the case of RIF and PANS-TB, it generated 94.2% and 92.2% sensitivity, which were lower than baseline model by 0.7% and 1.9%, respectively. t-SNE visualization shows that DeepAMR_cluster captures lineage-related clusters in the latent space.The details of source code are provided at http://www.robots.ox.ac.uk/∼davidc/code.php.Supplementary data are available at Bioinformatics online.
The implementation of next generation sequencing techniques, such as whole-genome sequencing (WGS), in tuberculosis (TB) research has enabled timely, cost-effective, and comprehensive insights into the genetic repertoire of the human pathogens of the Mycobacterium tuberculosis complex (MTBC). WGS data allow for detailed epidemiological analysis based on genomic distance of the MTBC strains under investigation, e.g., for tracing outbreaks; it can accelerate diagnostics by predicting drug resistance from a mutation catalogue (Fig 1). Indeed, specific mutations even permit predictions on the possible clinical treatment course and outcome [1–4].
Open in a separate window
Fig 1
Principle of pathogen-tailored individualized treatment design.
(A) Mutations are obtained from a whole-genome sequencing reference mapping approach that can be also transferred into a cgMLST for molecular outbreak surveillance. (B) Individual mutations are further interpreted towards their biological phenotype employing a validated consensus mutation catalogue. (C) When canonical and/or high-level resistance-conferring mutations are present, this drug should not be used. However, mutations associated with a moderate or intermediate resistance level may allow the use of drugs at increased doses. Moreover, mutations can be used to predict different treatment outcomes. Thus, by also considering phylogenetic benign mutations that do not confer resistance, a comprehensive molecular drug susceptibility profile could be inferred for a pathogen-tailored individualized treatment regimen in the future. cgMLST,core genome multilocus sequencing type; TB, tuberculosis.
The development of an effective vaccine is urgently needed to fight tuberculosis (TB) which is still the leading cause of death from a single infectious agent worldwide. One of the promising vaccine candidates M72/AS01E consists of two proteins subunits PepA and PPE18 coded by Rv0125 and Rv1196. However, preliminary data indicate a high level of sequence variability among clinical Mycobacterium tuberculosis complex (MTBC) strains that might have an impact on the vaccine efficacy. To further investigate this finding, we determined ppE18 sequence variability in a well-characterized reference collection of 71 MTBC strains from 23 phylogenetic lineages representing the global MTBC diversity. In total, 100 sequence variations consisting of 96 single nucleotide polymorphisms (SNPs), three insertions and one deletion were detected resulting in 141 variable positions distributed over the entire gene. The majority of SNPs detected were non-synonymous (n = 68 vs. n = 28 synonymous). Strains from animal adapted lineages, e.g., M. bovis, showed a significant higher diversity than the human pathogens such as M. tuberculosis Haarlem. SNP patterns specific for different lineages as well as for deeper branches in the phylogeny could be identified. The results of our study demonstrate a high variability of the ppE18 gene even in the N-terminal domains that is normally highly conserved in ppe genes. As the N-terminal region interacts with TLR2 receptor inducing a protective anti-inflammatory immune response, genetic heterogeneity has a potential impact on the vaccine efficiency, however, this has to be investigated in future studies.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
'%3e%3cpath fill='%23001489' d='M0 0v6h9V0z'/%3e%3cpath fill='%23e03c31' d='M0 0v3h9V0z'/%3e%3cg stroke='%23fff' stroke-width='2'%3e%3cpath id='d' d='m0 0 4.5 3L0 6m4.5-3H9'/%3e%3cuse xlink:href='%23b' stroke='%23ffb81c' clip-path='url(%23c)'/%3e%3c/g%3e%3cuse xlink:href='%23d' fill='none' stroke='%23007749' stroke-width='1.2'/%3e%3c/g%3e%3c/svg%3e)