Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences.
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ABSTRACT:
SUBMITTER: Coll F
PROVIDER: S-EPMC4446134 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences.
Coll Francesc F McNerney Ruth R Preston Mark D MD Guerra-Assunção José Afonso JA Warry Andrew A Hill-Cawthorne Grant G Mallard Kim K Nair Mridul M Miranda Anabela A Alves Adriana A Perdigão João J Viveiros Miguel M Portugal Isabel I Hasan Zahra Z Hasan Rumina R Glynn Judith R JR Martin Nigel N Pain Arnab A Clark Taane G TG
Genome medicine 20150527 1
Mycobacterium tuberculosis drug resistance (DR) challenges effective tuberculosis disease control. Current molecular tests examine limited numbers of mutations, and although whole genome sequencing approaches could fully characterise DR, data complexity has restricted their clinical application. A library (1,325 mutations) predictive of DR for 15 anti-tuberculosis drugs was compiled and validated for 11 of them using genomic-phenotypic data from 792 strains. A rapid online 'TB-Profiler' tool was ...[more]
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Project description:Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance.To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods.The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites.Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management.
| S-EPMC4804620 | biostudies-other
Project description:ObjectiveThe resistance of Mycobacterium (M.) tuberculosis to antituberculosis drugs poses a major threat to global public health. Whole genome sequencing (WGS) is an increasingly preferred method in the diagnostics and monitoring of the transmission dynamics of resistant forms of tuberculosis (TB). The aim of the study was to, for the first time, use the sequencing-based analysis to study the transmission and resistance patterns of a systematic and recent collection of extensively drug resistant (XDR) and multidrug resistant tuberculosis (MDR-TB) isolates and to expand our knowledge about drug resistant (DR) TB epidemiological dynamics in Slovakia.DesignA total of 495 patients with pulmonary TB, who were referred to National Reference Laboratory for Mycobacteriology (Vyšné Hágy, Slovakia) in the years 2018-2019, were studied. Out of the total of 495 patients, 4 XDR-TB (0.8%) and 8 (1.6%) MDR-TB isolates were identified by conventional drug susceptibility testing on Löwenstein-Jensen solid medium and subjected to whole genome sequencing. Sequencing data were evaluated for molecular-epidemiological analysis and identification of resistance patterns.ResultsPhylogenetic and cluster analysis showed extensive recent transmission events and the predominance of Euro-American lineage 4.7 in Slovakia. However, phylogenetic analysis revealed the circulation of several lineages that originally occurred in Eastern European countries. Resistance patterns for first- and second-line antituberculosis drugs characterized by whole genome sequencing were in high concordance with the results of phenotypic drug susceptibility testing.ConclusionForty percent of at least MDR-TB isolates were not genetically linked, indicating that appropriate measures should be taken to monitor and prevent the spread of drug-resistant tuberculosis within the country as well as in other regions.
| S-EPMC8717600 | biostudies-literature
Project description:The new molecular assay Xpert MTB/XDR (Cepheid, Sunnyvale, CA, USA) was launched in 2021 to detect Mycobacterium tuberculosis (MT) complex with mutations conferring resistance to isoniazid (INH), ethionamide (ETH), fluoroquinolone (FQ), and second-line injectable drugs (SLIDs). The aim of our study was to evaluate the performance of the Xpert MTB/XDR rapid molecular assay on rifampicin-resistant, multidrug-resistant, and pre-extensively resistant tuberculosis (TB) isolates in a clinical laboratory in the Balkan Peninsula compared to a phenotypic drug susceptibility test (pDST). Xpert MTB/XDR was used to test positive Bactec MGIT 960 (Becton, Dickinson and Co., Franklin Lakes, NJ, USA) cultures or DNA isolates. In the case of discrepant results between Xpert MTB/XDR and pDST, the usefulness of whole-genome sequencing (WGS) was emphasized. In our study, 80 MT isolates from different Balkan countries were selectively chosen from the National Mycobacterial Strain Collection in Golnik, Slovenia. Isolates were tested with the Xpert MTB/XDR assay, conventional pDST, and WGS. Xpert MTB/XDR showed high sensitivities of 91.9%, 100%, and 100% for detecting INH, FQ, and SLID resistance, respectively, compared to pDST. In contrast, low sensitivity (51.9%) for ETH resistance was achieved because isolates harbored widespread mutations across the ethA gene. The specificity of Xpert MTB/XDR was 100% for all drugs except for INH (66.7%). Further investigation with WGS revealed -57c→t mutations in the oxyR-ahpC region marked with uncertain significance, which caused the low specificity for detecting INH resistance with the new assay. Xpert MTB/XDR can be used in clinical laboratories for the rapid detection of INH, FQ, and SLID resistance. Moreover, it can be used to rule in resistance to ETH. Additional use of WGS is recommended in cases of discrepant results between pDST and Xpert MTB/XDR. Future improvements of Xpert MTB/XDR with the inclusion of additional genes may increase the usefulness of the assay. IMPORTANCE The Xpert MTB/XDR was tested on drug-resistant Mycobacterium tuberculosis complex isolates from the Balkan Peninsula. Positive Bactec MGIT 960 cultures or DNA isolates were tested as starting material. According to the results of our study with Xpert MTB/XDR, sensitivities for the detection of SLID, FQ, and INH resistance were sufficient (>90%) for the assay to be implemented into diagnostic algorithms. In our study, WGS revealed lesser-known mutations in genes conferring INH and ETH resistance, and their impact on resistance is still unknown. Mutations in the ethA gene causing resistance to ETH were scattered along structural gene without high-confidence markers for resistance. Therefore, resistance to ETH should be reported based on a combination of methods. Because the Xpert MTB/XDR assay was found to have good performance, we propose that it should be the method of choice for confirming resistance to INH, FQ, and SLID and conditionally for resistance to ETH.
| S-EPMC10100718 | biostudies-literature
Project description:BackgroundGenome-wide association studies (GWAS) have considerably advanced our understanding of human traits and diseases. With the increasing availability of whole genome sequences (WGS) for pathogens, it is important to establish whether GWAS of viral genomes could reveal important biological insights. Here we perform the first proof of concept viral GWAS examining drug resistance (DR), a phenotype with well understood genetics.MethodWe performed a GWAS of DR in a sample of 343 HIV subtype C patients failing 1st line antiretroviral treatment in rural KwaZulu-Natal, South Africa. The majority and minority variants within each sequence were called using PILON, and GWAS was performed within PLINK. HIV WGS from patients failing on different antiretroviral treatments were compared to sequences derived from individuals naïve to the respective treatment.ResultsGWAS methodology was validated by identifying five associations on a genetic level that led to amino acid changes known to cause DR. Further, we highlighted the ability of GWAS to identify epistatic effects, identifying two replicable variants within amino acid 68 of the reverse transcriptase protein previously described as potential fitness compensatory mutations. A possible additional DR variant within amino acid 91 of the matrix region of the Gag protein was associated with tenofovir failure, highlighting GWAS's ability to identify variants outside classical candidate genes. Our results also suggest a polygenic component to DR.ConclusionsThese results validate the applicability of GWAS to HIV WGS data even in relative small samples, and emphasise how high throughput sequencing can provide novel and clinically relevant insights. Further they suggested that for viruses like HIV, population structure was only minor concern compared to that seen in bacteria or parasite GWAS. Given the small genome length and reduced burden for multiple testing, this makes HIV an ideal candidate for GWAS.
| S-EPMC5038937 | biostudies-literature
Project description:Whole-genome sequencing allows rapid detection of drug-resistant Mycobacterium tuberculosis isolates. However, the availability of high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been limited. We determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from the Democratic Republic of the Congo, Ivory Coast, Peru, Thailand, and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD Bactec MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared DST results with predicted drug resistance profiles inferred by whole-genome sequencing. Classification of strains by the two phenotypic DST methods into resistotype/wild-type populations was concordant in 73 to 99% of cases, depending on the drug. Our data suggest that the established critical concentration (5?mg/liter) for ethambutol resistance (MGIT 960 system) is too high and misclassifies strains as susceptible, unlike 7H10 agar dilution. Increased minimal inhibitory concentrations were explained by mutations identified by whole-genome sequencing. Using whole-genome sequences, we were able to predict quantitative drug resistance levels for the majority of drug resistance mutations. Predicting quantitative levels of drug resistance by whole-genome sequencing was partially limited due to incompletely understood drug resistance mechanisms. The overall sensitivity and specificity of whole-genome-based DST were 86.8% and 94.5%, respectively. Despite some limitations, whole-genome sequencing has the potential to infer resistance profiles without the need for time-consuming phenotypic methods.
| S-EPMC6496161 | biostudies-literature
Project description:Understanding the circulating Mycobacterium tuberculosis resistance mutations is vital for better TB control strategies, especially to inform a new MDR-TB treatment programme. We complemented the phenotypic drug susceptibility testing (DST) based drug resistance surveys (DRSs) conducted in Uganda between 2008 and 2011 with Whole Genome Sequencing (WGS) of 90 Mycobacterium tuberculosis isolates phenotypically resistant to rifampicin and/or isoniazid to better understand the extent of drug resistance. A total of 31 (34.4 %) patients had MDR-TB, 5 (5.6 %) mono-rifampicin resistance and 54 (60.0 %) mono-isoniazid resistance by phenotypic DST. Pyrazinamide resistance mutations were identified in 32.3% of the MDR-TB patients. Resistance to injectable agents was detected in 4/90 (4.4%), and none to fluoroquinolones or novel drugs. Compensatory mutations in rpoC were identified in two patients. The sensitivity and specificity of drug resistance mutations compared to phenotypic DST were for rpoB 88.6% and 98.1%, katG 60.0% and 100%, fabG1 16.5% and 100%, katG and/or fabG1 71.8% and 100%, embCAB 63.0% and 82.5%, rrs 11.4% and 100%, rpsL 20.5% and 95.7% and rrs and/or rpsL 31.8% and 95.7%. Phylogenetic analysis showed dispersed MDR-TB isolate, with only one cluster of three Beijing family from South West Uganda. Among tuberculosis patients in Uganda, resistance beyond first-line drugs as well as compensatory mutations remain low, and MDR-TB isolates did not arise from a dominant clone. Our findings show the potential use of sequencing for complementing DRSs or surveillance in this setting, with good specificity compared to phenotypic DST. The reported high confidence mutations can be included in molecular assays, and population-based studies can track transmission of MDR-TB including the Beijing family strains in the South West of the country.
| S-EPMC4856735 | biostudies-literature
Project description:We investigated the lineages of Mycobacterium tuberculosis (Mtb) isolates from the RYOKEN study in Japan in 2007 and the usefulness of genotypic drug susceptibility testing (DST) using the Genome Research for Asian Tuberculosis (GReAT) database. In total, 667 isolates were classified into lineage 1 (4.6%), lineage 2 (0.8%), lineage 2/Beijing (72.1%), lineage 3 (0.5%), and lineage 4 (22.0%). The nationality, gender, and age groups associated with the isolates assigned to lineage 1 were significantly different from those associated with other lineages. In particular, isolates of lineage 1.2.1 (EAI2) formed sub-clusters and included a 2,316-bp deletion in the genome. The proportion of the isolates resistant to at least one anti-tuberculosis (TB) drug was 10.8%, as determined by either the genotypic or phenotypic method of DST. However, the sensitivities to isoniazid, streptomycin, and ethambutol determined by the genotypic method were low. Thus, unidentified mutations in the genome responsible for drug resistance were explored, revealing previously unreported mutations in the katG, gid, and embB genes. This is the first nationwide report of whole-genome analysis of TB in Japan.
| S-EPMC6731343 | biostudies-literature
Project description: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.
| S-EPMC6775242 | biostudies-literature
Project description:Background: Whole-genome sequencing (WGS) is a viable and financially feasible tool for timely and comprehensive diagnosis of drug resistance in developed countries. With the increase in the incidence of multidrug-resistant tuberculosis (MDR-TB), second-line anti-TB drugs are gaining importance. However, genetic resistance to second-line anti-TB drugs based on WGS has not been fully studied. Methods: We randomly selected 100 MDR-TB and 10 non-MDR-TB isolates from a hospital in Zhejiang Province, China. Drug susceptibility tests against 13 anti-TB drugs were performed, and 34 drug resistance-related genes were analyzed using WGS in all isolates. For each drug, the accuracy, sensitivity, specificity, and positive and negative predictive values of WGS were compared with those of the conventional drug susceptibility test. Results: The overall sensitivity and specificity for WGS were respectively, 99.0 and 100.0% for isoniazid (INH), 99.0 and 100.0% for rifampicin (RIF), 94.8 and 65.3% for ethambutol (EMB), 86.2 and 84.4% for pyrazinamide (PZA), 95.6 and 95.6% for levofloxacin (LFX), 89.5 and 65.3% for moxifloxacin (MFX), 91.3 and 95.1% for streptomycin (SM), 90.9 and 99.0% for kanamycin, 90.9 and 100.0% for amikacin, 88.9 and 98.0% for capreomycin, 87.0 and 85.1% for prothionamide (PTO), 85.7 and 99.0% for para-aminosalicylic acid (PAS), and 66.7 and 95.9% for clofazimine (CLO). Conclusions: WGS is a promising approach to predict resistance to INH, RIF, PZA, LFX, SM, second-line injectable drugs (SLIDs), and PTO with satisfactory accuracy, sensitivity, and specificity of over 85.0%. The specificity of WGS in diagnosing resistance to EMB, and high-level resistance to MFX (2.0 mg/L) needs to be improved.
| S-EPMC6685394 | biostudies-literature
Project description:Before 2013, 92 countries reported extensively drug-resistant Mycobacterium tuberculosis cases to the WHO. Here, we announce the genome sequences of two clinical isolates of extensively drug-resistant tuberculosis (XDR-TB) from Zunyi, China. The genome sequences are composed of 4,411,507 bp and 4,411,515 bp with 2,210 and 2,071 variants, respectively, when compared to the H37Rv genome.
| S-EPMC4172270 | biostudies-literature