A comprehensive characterization of PncA polymorphisms that confer resistance to pyrazinamide

A simplified pyrazinamidase test for Mycobacterium tuberculosis pyrazinamide antimicrobial susceptibility testing

Pyrazinamide (PZA) is an important first-line drug for tuberculosis (TB) treatment by eradicating the persisting Mycobacterium tuberculosis complex (MTBC). Due to cost and technical challenges, end TB strategies are hampered by the lack of a simple and reliable culture-based PZA antimicrobial susceptibility testing (AST) for routine use. We initially developed a simplified chromogenic pyrazinamidase (PZase) test in the TB reference laboratory using a training set MTBC isolates with various drug-resistant profiles, and validated its performance using consecutive BACTEC MGIT 960 (MGIT)-culture-positive culture in 10 clinical laboratories. The pncA gene Sanger sequencing results were used as the reference, and compared to the MGIT-PZA AST. Differential diagnosis of Mycobacterium bovis was conducted using patented in-house real-time PCR. Of the 106 training isolates, the PZase test and MGIT-PZA AST showed 100.0% and 99.1% concordance as compared to Sanger sequencing, respectively. We found 32.1% (34/106) isolates harbored pncA mutations, including one isolate with silent mutation S65S. For validation, 1,793 clinical isolates were tested including 150 duplicate isolates from specimens of the same cases and 16 isolates with uncharacterized drug resistance (UDR)-associated mutations. Excluding duplicated and UDR isolates, we identified 2.6% (43/1,627) PZA-resistant isolates, including 1.3% (21/1,627) M. bovis isolates. The kappa values were 0.851-1.000. In addition, the accuracy of the PZase test conducted by 10 laboratories was 98.5%-100.0%. Our simplified PZase test demonstrated high concordance with Sanger sequencing and MGIT-PZA AST. Integrating the PZase test into routine first-line AST is effortless and represents an improvement in laboratory services for ending TB.

IMPORTANCE

We developed and validated a simple pyrazinamidase (PZase) test for pyrazinamide (PZA) antimicrobial susceptibility testing (AST). Our results demonstrated that the PZase test had high agreement with the pncA gene sequencing and MGIT-PZA AST. Integrating PZase test into routine AST is effortless and represents an improvement in laboratory services for ending TB.

ResMAP-a saturation mutagenesis platform enabling parallel profiling of target-specific resistance-conferring mutations in Plasmodium

New and improved drugs are required for the treatment and ultimate eradication of malaria. The efficacy of front-line therapies is now threatened by emerging drug resistance; thus, new tools to support the development of drugs with a lower propensity for resistance are needed. Here, we describe the development of a RESistance Mapping And Profiling (ResMAP) platform for the identification of resistance-conferring mutations in Plasmodium drug targets. Proof-of-concept studies focused on interrogating the antimalarial drug target, Plasmodium falciparum lysyl tRNA synthetase (PfKRS). Saturation mutagenesis was used to construct a plasmid library encoding all conceivable mutations within a 20-residue span at the base of the PfKRS ATP-binding pocket. The superior transfection efficiency of Plasmodium knowlesi was exploited to generate a high coverage parasite library expressing PfKRS bearing all possible amino acid changes within this region of the enzyme. The selection of the library with PfKRS inhibitors, cladosporin and DDD01510706, successfully identified multiple resistance-conferring substitutions. Genetic validation of a subset of these mutations confirmed their direct role in resistance, with computational modeling used to dissect the structural basis of resistance. The application of ResMAP to inform the development of resistance-resilient antimalarials of the future is discussed.

IMPORTANCE

An increase in treatment failures for malaria highlights an urgent need for new tools to understand and minimize the spread of drug resistance. We describe the development of a RESistance Mapping And Profiling (ResMAP) platform for the identification of resistance-conferring mutations in Plasmodium spp, the causative agent of malaria. Saturation mutagenesis was used to generate a mutation library containing all conceivable mutations for a region of the antimalarial-binding site of a promising drug target, Plasmodium falciparum lysyl tRNA synthetase (PfKRS). Screening of this high-coverage library with characterized PfKRS inhibitors revealed multiple resistance-conferring substitutions including several clinically relevant mutations. Genetic validation of these mutations confirmed resistance of up to 100-fold and computational modeling dissected their role in drug resistance. We discuss potential applications of this data including the potential to design compounds that can bypass the most serious resistance mutations and future resistance surveillance.

Integrating bacterial molecular genetics with chemical biology for renewed antibacterial drug discovery

The application of dyes to understanding the aetiology of infection inspired antimicrobial chemotherapy and the first wave of antibacterial drugs. The second wave of antibacterial drug discovery was driven by rapid discovery of natural products, now making up 69% of current antibacterial drugs. But now with the most prevalent natural products already discovered, ∼107 new soil-dwelling bacterial species must be screened to discover one new class of natural product. Therefore, instead of a third wave of antibacterial drug discovery, there is now a discovery bottleneck. Unlike natural products which are curated by billions of years of microbial antagonism, the vast synthetic chemical space still requires artificial curation through the therapeutics science of antibacterial drugs - a systematic understanding of how small molecules interact with bacterial physiology, effect desired phenotypes, and benefit the host. Bacterial molecular genetics can elucidate pathogen biology relevant to therapeutics development, but it can also be applied directly to understanding mechanisms and liabilities of new chemical agents with new mechanisms of action. Therefore, the next phase of antibacterial drug discovery could be enabled by integrating chemical expertise with systematic dissection of bacterial infection biology. Facing the ambitious endeavour to find new molecules from nature or new-to-nature which cure bacterial infections, the capabilities furnished by modern chemical biology and molecular genetics can be applied to prospecting for chemical modulators of new targets which circumvent prevalent resistance mechanisms.

Biphasic Medium Using Nicotinamide for Detection of Pyrazinamide Resistance in Mycobacterium tuberculosis

Reliable drug susceptibility testing of pyrazinamide (PZA) is technically difficult, since PZA activity is pH sensitive. The aim of this study was to evaluate a biphasic medium assay (BMA) for the reliable detection of PZA resistance in Mycobacterium tuberculosis (MTB) using nicotinamide (NIC) as a surrogate for PZA and identifying the appropriate cut-off value for the assay. The PZA susceptibility of 122 multidrug-resistant tuberculosis (MDR-TB) isolates and 39 drug-susceptible tuberculosis (DS-TB) isolates was examined using the BMA with NIC at four different concentrations (250, 500, 1000, and 2000 mg/L) and comparing the results with results from the BACTEC MGIT 960 reference method. Out of 122 MDR-TB isolates, 40 were identified as resistant by the BACTEC MGIT 960 system, of which 92.5% contained mutations within their pncA gene plus promoter region. A minimum inhibitory concentration of NIC ≥ 1000 mg/L was used as the cut-off concentration to define resistance in correlation with the MGIT 960 outcomes. NIC-BMA had a sensitivity of 90.91%, a specificity of 100%, and an accuracy of 97.52% compared with the MGIT 960 method. NIC-BMA is a promising assay to screen PZA resistance in microbiological laboratories without automation or advanced molecular instruments.

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region's significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

A robust computational quest: Discovering potential hits to improve the treatment of pyrazinamide-resistant Mycobacterium tuberculosis

The rise of pyrazinamide (PZA)-resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA-resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost-effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments.

Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine-learning approaches

Background

Pyrazinamide is one of four first-line antibiotics used to treat tuberculosis; however, antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation in pncA, encoding an enzyme that converts pyrazinamide into its active form.

Methods

We curated a dataset of 664 non-redundant, missense amino acid mutations in PncA with associated high-confidence phenotypes from published studies and then trained three different machine-learning models to predict pyrazinamide resistance. All models had access to a range of protein structural-, chemical- and sequence-based features.

Results

The best model, a gradient-boosted decision tree, achieved a sensitivity of 80.2% and a specificity of 76.9% on the hold-out test dataset. The clinical performance of the models was then estimated by predicting the binary pyrazinamide resistance phenotype of 4027 samples harbouring 367 unique missense mutations in pncA derived from 24 231 clinical isolates.

Conclusions

This work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs.

Prevalence, Transmission and Genetic Diversity of Pyrazinamide Resistance Among Multidrug-Resistant Mycobacterium tuberculosis Isolates in Hunan, China

Background

China is a country with a burden of high rates of both TB and multidrug-resistant TB (MDR-TB). However, published data on pyrazinamide (PZA) resistance are still limited in Hunan province, China. This study investigated the prevalence, transmission, and genetic diversity of PZA resistance among multidrug-resistant Mycobacterium tuberculosis isolates in Hunan province.

Methods

Drug susceptibility testing (DST) with the Bactec MGIT 960 PZA kit and pyrazinamidase (PZase) testing were conducted on all 298 MDR clinical isolates. Moreover, 24-locus MIRU-VNTR and DNA sequencing of pncA, rpsA, and panD genes were conducted on 180 PZA-resistant (PZA-R) isolates.

Results

The prevalence of PZA resistance among MDR-TB strains reached 60.4%. Newly diagnosed PZA-R TB patients and clustered isolates with identical pncA, rpsA, and panD mutations showed that transmission of PZA-R isolates played a significant role in the formation of PZA-R TB. Ninety-eight mutation patterns were observed in the pncA among 180 PZA-R isolates, and seventy-one (72.4%) were point mutations. Twenty-four of these mutations are new, including 2 base substitutions (V93G and T153S) and 22 nucleotide deletions or insertions. The W119C was found in PZA-S isolates, on the other hand, F94L and V155A mutations were found in both PZA resistant and susceptible isolates with positive PZase activity, indicating that they were not associated with PZA resistance. This is not entirely in line with the WHO catalogue. Ten novel rpsA mutations were found in 10 PZA-R isolates, which all combined with mutations in pncA. Thus, it is unpredictable whether these mutations in rpsA can impact PZA resistance. No panD mutation was found in all PZA-R isolates.

Conclusion

DNA sequencing of pncA and PZase activity testing have great potential in predicting PZA resistance.

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

The World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis. However, molecular diagnostics to date have focused largely on first-line drugs and predicting susceptibilities in a binary manner (classifying strains as either susceptible or resistant). Here, we used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration (MIC) in 15,211 Mycobacterium tuberculosis clinical isolates from 23 countries across five continents. We identified 492 unique MIC-elevating variants across 13 drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms.

Clinical Significance of Preoperative Pyrazinamide-Containing Therapy in Tuberculous Constrictive Pericarditis

Background

Tuberculous constrictive pericarditis (TCP) is recommended to be treated with anti-tuberculosis (TB) therapy before pericardiectomy. Whether different preoperative anti-TB regimens may lead to different outcomes is unclear.

Methods

We retrospectively collected patients diagnosed as TCP and received pericardiectomy from April 2016 to June 2023. The study patients were assigned into the active TCP (A-TCP) group and the inactive TCP (IA-TCP) group according to the results of Mycobacterium tuberculosis (MTB) culture and MTB RNA assay. Baseline characteristics including anti-TB regimens and surgical outcomes were compared between the two groups. Logistic regression analysis and subgroup analysis were conducted to identify the protective factors of A-TCP.

Results

Of the 102 study patients, 24 was in the A-TCP group and 78 was in the IA-TCP group. The rate of preoperative anti-TB regimen containing pyrazinamide was 37.5% in the A-TCP group, as compared with 74.4% in the IA-TCP group (P = 0.001). Multivariate analysis showed that preoperative use of pyrazinamide was the protective factor of A-TCP (OR 0.194, 95% CI 0.053-0.703, P = 0.013). Subgroup analysis based on age also showed consistent findings. In the analyses of surgical outcomes, A-TCP was the independent risk factor of postoperative cardiac complications (OR 4.231, 95% CI 1.317-13.593, P = 0.015) and associated with longer hospital stay (P = 0.004) and higher hospitalization cost (P = 0.001).

Conclusion

A strategy involving anti-TB regimen containing pyrazinamide before pericardiectomy was superior to that without pyrazinamide in the patients with TCP. The strategy was associated with lower risk of A-TCP and might lead to better postoperative recovery and cost-effectiveness.

Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of Mycobacterium tuberculosis

Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating Mycobacterium tuberculosis (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of pncA gene product pyrazinamidase (PZase) activity. Mutations occurred in pncA are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA.Communicated by Ramaswamy H. Sarma.

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

The World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis; however, molecular diagnostics to date have focused largely on first-line drugs and predicting binary susceptibilities. We used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration in 15,211 Mycobacterium tuberculosis patient isolates from 23 countries across five continents. This identified 492 unique MIC-elevating variants across thirteen drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms.

Drug resistance prediction for Mycobacterium tuberculosis with reference graphs

Tuberculosis is a global pandemic disease with a rising burden of antimicrobial resistance. As a result, the World Health Organization (WHO) has a goal of enabling universal access to drug susceptibility testing (DST). Given the slowness of and infrastructure requirements for phenotypic DST, whole-genome sequencing, followed by genotype-based prediction of DST, now provides a route to achieving this. Since a central component of genotypic DST is to detect the presence of any known resistance-causing mutations, a natural approach is to use a reference graph that allows encoding of known variation. We have developed DrPRG (Drug resistance Prediction with Reference Graphs) using the bacterial reference graph method Pandora. First, we outline the construction of a Mycobacterium tuberculosis drug resistance reference graph. The graph is built from a global dataset of isolates with varying drug susceptibility profiles, thus capturing common and rare resistance- and susceptible-associated haplotypes. We benchmark DrPRG against the existing graph-based tool Mykrobe and the haplotype-based approach of TBProfiler using 44 709 and 138 publicly available Illumina and Nanopore samples with associated phenotypes. We find that DrPRG has significantly improved sensitivity and specificity for some drugs compared to these tools, with no significant decreases. It uses significantly less computational memory than both tools, and provides significantly faster runtimes, except when runtime is compared to Mykrobe with Nanopore data. We discover and discuss novel insights into resistance-conferring variation for M. tuberculosis - including deletion of genes katG and pncA - and suggest mutations that may warrant reclassification as associated with resistance.

Mutation bias and the predictability of evolution

Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Online Service with Automated Interpretation of Sequencing Data and Prediction of Pyrazinamide Resistance in Mycobacterium tuberculosis

Pyrazinamide plays an important role in the treatment of tuberculosis. However, the microbiological test for pyrazinamide resistance is more complex and less reliable than testing of susceptibility to other anti-tuberculosis drugs due to the need to grow the pathogen at pH 5.5. Identification of mutations that cause resistance to anti-tuberculosis drugs can replace microbiological methods. Mutations in the pncA gene are responsible for the main mechanism of the resistance to pyrazinamide and are found in more than 90% of resistant strains. However, the genetic method for determining drug susceptibility is very complex, because mutations leading to pyrazinamide resistance are diverse and scattered throughout the gene. We have developed a software package for automatic data interpretation and prediction of the resistance to pyrazinamide based on Sanger sequencing results. The effectiveness of detection of pyrazinamide resistance in 16 clinical samples was compared using the BACTEC MGIT 960 automated system and pncA gene Sanger sequencing with automated analysis of the results. A significant advantage of the developed method over a single microbiological study was shown, due to greater reliability of the results irrespective of the purity of isolates.

Pyrazinamide-resistant Tuberculosis Obscured From Common Targeted Molecular Diagnostics

Here, we describe a clinical case of pyrazinamide-resistant (PZA-R) tuberculosis (TB) reported as PZA-susceptible (PZA-S) by common molecular diagnostics. Phenotypic susceptibility testing (pDST) indicated PZA-R TB. Targeted Sanger sequencing reported wild-type PncA, indicating PZA-S TB. Whole Genome Sequencing (WGS) by PacBio and IonTorrent both detected deletion of a large portion of pncA, indicating PZA-R. Importantly, both WGS methods showed deletion of part of the primer region targeted by Sanger sequencing. Repeating Sanger sequencing from a culture in presence of PZA returned no result, revealing that 1) two minority susceptible subpopulations had vanished, 2) the PZA-R majority subpopulation harboring the pncA deletion could not be amplified by Sanger primers, and was thus obscured by amplification process. This case demonstrates how a small susceptible subpopulation can entirely obscure majority resistant populations from targeted molecular diagnostics and falsely imply homogenous susceptibility, leading to incorrect diagnosis. To our knowledge, this is the first report of a minority susceptible subpopulation masking a majority resistant population, causing targeted molecular diagnostics to call false susceptibility. The consequence of such genomic events is not limited to PZA. This phenomenon can impact molecular diagnostics' sensitivity whenever the resistance-conferring mutation is not fully within primer-targeted regions. This can be caused by structural changes of genomic context with phenotypic consequence as we report here, or by uncommon mechanisms of resistance. Such false susceptibility calls promote suboptimal treatment and spread of strains that challenge targeted molecular diagnostics. This motivates development of molecular diagnostics unreliant on primer conservation, and impels frequent WGS surveillance for variants that evade prevailing molecular diagnostics.

Mutations Associated with Pyrazinamide Resistance in Mycobacterium tuberculosis: A Review and Update

Pyrazinamide (PZA) has remained a keystone of tuberculosis (TB) therapy, and it possesses high imperative sterilizing action that can facilitate reduction in the present chemotherapy regimen. The combination of PZA works both with first- and second-line TB drugs, notably fluoroquinolones, clofazimine, bedaquiline, delamanid and pretomanid. Pyrazinamide inhibits various targets that are involved in different cellular processes like energy production (pncA), trans-translation (rpsA) and pantothenate/coenzyme A (panD) which are required for persistence of the pathogen. It is well known that pncA gene encoding pyrazinamidase is involved in the transition of PZA into the active form of pyrazinoic acid, which implies that mutation in the pncA gene can develop PZA resistance in Mycobacterium tuberculosis (M. tuberculosis) strain leading to a major clinical and public health concern. Therefore, it is very crucial to understand its resistance mechanism and to detect it precisely to help in the management of the disease. Scope of this review is to have a deep understanding of molecular mechanism of PZA resistance with its multiple targets which would help study the association of mutations and its resistance in M. tuberculosis. This will in turn help learn about the resistance of PZA and develop more accurate molecular diagnostic tool for drug-resistant TB in future TB therapy.

Detection of Mutations in pncA in Mycobacterium tuberculosis Clinical Isolates from Nepal in Association with Pyrazinamide Resistance

Without the proper information on pyrazinamide (PZA) susceptibility of Mycobacterium tuberculosis (MTB), PZA is inappropriately recommended for the treatment of both susceptible and multidrug-resistant tuberculosis (MDR-TB) in Nepal. This study aimed to collect information regarding PZA susceptibility in MTB isolates from Nepal by analyzing pncA and its upstream regulatory region (URR). A total of 211 MTB isolates were included in this study. Sequence analysis of pncA and its URR was performed to assess PZA resistance. First-line drug susceptibility testing, spoligotyping, and sequence analysis of rpoB, katG, the inhA regulatory region, gyrA, gyrB, and rrs were performed to assess their association with pncA mutation. Sequencing results reveal that 125 (59.2%) isolates harbored alterations in pncA and its URR. A total of 57 different mutation types (46 reported and 11 novel) were scattered throughout the whole length of the pncA gene. Eighty-seven isolates (41.2%) harbored mutations in pncA, causing PZA resistance in MTB. There was a more significant association of pncA alterations in MDR/pre-extensively drug-resistant (Pre-XDR) TB than in mono-resistant/pan-susceptible TB (p < 0.005). This first report on the increasing level of PZA resistance in DR-TB in Nepal highlights the importance of PZA susceptibility testing before DR-TB treatment.

A CRISPR-guided mutagenic DNA polymerase strategy for the detection of antibiotic-resistant mutations in M. tuberculosis

A sharp increase in multidrug-resistant tuberculosis (MDR-TB) threatens human health. Spontaneous mutation in essential gene confers an ability of Mycobacterium tuberculosis resistance to anti-TB drugs. However, conventional laboratory strategies for identification and prediction of the mutations in this slowly growing species remain challenging. Here, by combining XCas9 nickase and the error-prone DNA polymerase A from M. tuberculosis, we constructed a CRISPR-guided DNA polymerase system, CAMPER, for effective site-directed mutagenesis of drug-target genes in mycobacteria. CAMPER was able to generate mutagenesis of all nucleotides at user-defined loci, and its bidirectional mutagenesis at nick sites allowed editing windows with lengths up to 80 nucleotides. Mutagenesis of drug-targeted genes in Mycobacterium smegmatis and M. tuberculosis with this system significantly increased the fraction of the antibiotic-resistant bacterial population to a level approximately 60- to 120-fold higher than that in unedited cells. Moreover, this strategy could facilitate the discovery of the mutation conferring antibiotic resistance and enable a rapid verification of the growth phenotype-mutation genotype association. Our data demonstrate that CAMPER facilitates targeted mutagenesis of genomic loci and thus may be useful for broad functions such as resistance prediction and development of novel TB therapies.

In Silico Drug Designing for ala438 Deleted Ribosomal Protein S1 (RpsA) on the Basis of the Active Compound Zrl15

Pyrazinoic acid-resistant tuberculosis is a severe chronic disorder. First-line drugs specifically target the ribosomal protein subunit-1 (RpsA) and stop trans-translation in the wild-type bacterium, causing bacterial cell death. In mutant bacterial strain, the deletion of ala438 does not let the pyrazinoic acid to bind to the active site of RpsA and ensures that the bacterium survives. Hence, such tuberculosis cases require an immediate and successful regime. The current study was designed to identify inhibitors that could bind to the mutant state of the RpsA protein. Initially, a pharmacophore model was generated based on the recently published most potent inhibitor for the mutant state of RpsA, i.e., zrl15. The validated pharmacophore model was further used for virtual screening of two chemical libraries, i.e., ZINC and ChemBridge. After applying the Lipinski rule of five (Ro5), a total of 260 and 749 hits from the ChemBridge and ZINC libraries, respectively, were identified using pharmacophore mapping. These hits were then docked into the active site of the mutant state of the RpsA protein, and later, the top 150 compounds from each library were chosen based on the docking score. A total of 21 compounds were shortlisted from each library based on the best protein-ligand interactions. Finally, a total of 05 compounds were subjected to molecular dynamics study to examine the dynamic behavior of each compound in the active site of the mutant state of the RpsA protein. The results revealed that all compounds had good chemical properties such as absorption, distribution, metabolism, excretion, and toxicity (ADMET), and there was no Pan Assay Interference (PAINS) or deviation from Ro5, indicating that these compounds could be useful antagonists for the mutant state of the RpsA protein.

Comparative Performance of Genomic Methods for the Detection of Pyrazinamide Resistance and Heteroresistance in Mycobacterium tuberculosis

Pyrazinamide is an important component of both drug-susceptible and drug-resistant tuberculosis treatment regimens. Although approximately 50% of rifampin-resistant isolates are also resistant to pyrazinamide, pyrazinamide susceptibility testing is not routinely performed due to the challenging nature of the assay. We investigated the diagnostic accuracy of genotypic and phenotypic methods and explored the occurrence of pyrazinamide heteroresistance. We assessed pyrazinamide susceptibility among 358 individuals enrolled in the South African EXIT-RIF cohort using Sanger and targeted deep sequencing (TDS) of the pncA gene, whole-genome sequencing (WGS), and phenotypic drug susceptibility testing. We calculated the diagnostic accuracy of the different methods and investigated the prevalence and clinical impact of pncA heteroresistance. True pyrazinamide susceptibility status was assigned to each isolate using the Köser classification and expert rules. We observed 100% agreement across genotypic methods for detection of pncA fixed mutations; only TDS confidently identified three isolates (0.8%) with minor variants. For the 355 (99.2%) isolates that could be assigned true pyrazinamide status with confidence, phenotypic DST had a sensitivity of 96.5% (95% confidence interval [CI], 93.8 to 99.3%) and specificity of 100% (95% CI, 100 to 100%), both Sanger sequencing and WGS had a sensitivity of 97.1% (95% CI, 94.6 to 99.6%) and specificity of 97.8% (95% CI, 95.7 to 99.9%), and TDS had sensitivity of 98.8% (95% CI, 97.2 to 100%) and specificity of 97.8% (95% CI, 95.7 to 99.9%). We demonstrate high sensitivity and specificity for pyrazinamide susceptibility testing among all assessed genotypic methods. The prevalence of pyrazinamide heteroresistance in Mycobacterium tuberculosis isolates was lower than that identified for other first-line drugs.

GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning

BACKGROUND

Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens.

RESULTS

We present Translational Genomics platform for Tuberculosis (GenTB), a free and open web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tuberculosis drugs, respectively. We benchmark GenTB's predictive performance along with leading TB resistance prediction tools (Mykrobe and TB-Profiler) using a ground truth dataset of 20,408 isolates with laboratory-based drug susceptibility data. All four tools reliably predicted resistance to first-line tuberculosis drugs but had varying performance for second-line drugs. The mean sensitivities for GenTB-RF and GenTB-WDNN across the nine shared drugs were 77.6% (95% CI 76.6-78.5%) and 75.4% (95% CI 74.5-76.4%), respectively, and marginally higher than the sensitivities of TB-Profiler at 74.4% (95% CI 73.4-75.3%) and Mykrobe at 71.9% (95% CI 70.9-72.9%). The higher sensitivities were at an expense of ≤ 1.5% lower specificity: Mykrobe 97.6% (95% CI 97.5-97.7%), TB-Profiler 96.9% (95% CI 96.7 to 97.0%), GenTB-WDNN 96.2% (95% CI 96.0 to 96.4%), and GenTB-RF 96.1% (95% CI 96.0 to 96.3%). Averaged across the four tools, genotypic resistance sensitivity was 11% and 9% lower for isoniazid and rifampicin respectively, on isolates sequenced at low depth (< 10× across 95% of the genome) emphasizing the need to quality control input sequence data before prediction. We discuss differences between tools in reporting results to the user including variants underlying the resistance calls and any novel or indeterminate variants CONCLUSIONS: GenTB is an easy-to-use online tool to rapidly and accurately predict resistance to anti-tuberculosis drugs. GenTB can be accessed online at https://gentb.hms.harvard.edu , and the source code is available at https://github.com/farhat-lab/gentb-site .

Phenotypic and molecular characterization of pyrazinamide resistance among multidrug-resistant Mycobacterium tuberculosis isolates in Ningbo, China

Background

Detection of pyrazinamide (PZA) resistance in Mycobacterium tuberculosis (TB) patients is critical, especially in dealing with multidrug-resistant Mycobacterium tuberculosis (MDR-TB) case. Up to date, PZA drug susceptibility testing (DST) has not been regularly performed in China. The prevalence and molecular characteristics of PZA resistance in M.tuberculosis isolates, especially MDR-TB have not been studied in Ningbo, China. This study aimed to analyze the phenotypic and molecular characterization of PZA resistance among MDR-TB isolates in Ningbo.

Methods

A total of 110 MDR-TB isolates were collected from the TB patients who were recorded at local TB dispensaries in Ningbo. All clinical isolates were examined by drug susceptibility testing and genotyping. DNA sequencing was used to detect mutations in the pncA gene associated with PZA resistance.

Results

The prevalence of PZA resistance among MDR-TB strains in Ningbo was 59.1%. With regard to the history and the outcome of treatments among MDR-TB cases, the percentages of re-treated MDR-TB patients in the PZA-resistant group and of successful patients in PZA-susceptible group were significantly higher than the ones in the PZA-susceptible group and in the PZA-resistant group, respectively (P = 0.027, P = 0.020). The results showed that the resistance of streptomycin (67.7% vs 46.7%, P = 0.027), ethambutol (56.9% vs 33.3%, P = 0.015), ofloxacin (43.1% vs 11.1%, P = 0.000), levofloxacin (43.1% vs 11.1%, P = 0.000), pre-XDR (pre-Xtensively Drug Resistance) (38.5% vs 15.6%, P = 0.009), were more frequently adverted among PZA-resistant isolates compared with PZA-susceptible isolates. In addition, 110 MDR-TB was composed of 87 (PZA resistant, 78.5%) Beijing strains and 23 (PZA resistant, 21.5%) non-Beijing strains. Fifty-four out of 65 (83.1%) PZA-resistant MDR strains harbored a mutation located in the pncA gene and the majority (90.7%) were point mutations. Compared with the phenotypic characterization, DNA sequencing of pncA has sensitivity and specificity of 83.1 and 95.6%.

Conclusion

The mutations within pncA gene was the primary mechanism of PZA resistance among MDR-TB and DNA sequencing of pncA gene could provide a rapid detection evidence in PZA drug resistance of MDR-TB in Ningbo.

Quantifying transmission fitness costs of multi-drug resistant tuberculosis

As multi-drug resistant tuberculosis (MDR-TB) continues to spread, investigating the transmission potential of different drug-resistant strains becomes an ever more pressing topic in public health. While phylogenetic and transmission tree inferences provide valuable insight into possible transmission chains, phylodynamic inference combines evolutionary and epidemiological analyses to estimate the parameters of the underlying epidemiological processes, allowing us to describe the overall dynamics of disease spread in the population. In this study, we introduce an approach to Mycobacterium tuberculosis (M. tuberculosis) phylodynamic analysis employing an existing computationally efficient model to quantify the transmission fitness costs of drug resistance with respect to drug-sensitive strains. To determine the accuracy and precision of our approach, we first perform a simulation study, mimicking the simultaneous spread of drug-sensitive and drug-resistant tuberculosis (TB) strains. We analyse the simulated transmission trees using the phylodynamic multi-type birth-death model (MTBD, (Kühnert et al., 2016)) within the BEAST2 framework and show that this model can estimate the parameters of the epidemic well, despite the simplifying assumptions that MTBD makes compared to the complex TB transmission dynamics used for simulation. We then apply the MTBD model to an M. tuberculosis lineage 4 dataset that primarily consists of MDR sequences. Some of the MDR strains additionally exhibit resistance to pyrazinamide - an important first-line anti-tuberculosis drug. Our results support the previously proposed hypothesis that pyrazinamide resistance confers a transmission fitness cost to the bacterium, which we quantify for the given dataset. Importantly, our sensitivity analyses show that the estimates are robust to different prior distributions on the resistance acquisition rate, but are affected by the size of the dataset - i.e. we estimate a higher fitness cost when using fewer sequences for analysis. Overall, we propose that MTBD can be used to quantify the transmission fitness cost for a wide range of pathogens where the strains can be appropriately divided into two or more categories with distinct properties.

Insights Into Mutations Induced Conformational Changes and Rearrangement of Fe2+ Ion in pncA Gene of Mycobacterium tuberculosis to Decipher the Mechanism of Resistance to Pyrazinamide

Pyrazinamide (PZA) is the first-line drug commonly used in treating Mycobacterium tuberculosis (Mtb) infections and reduces treatment time by 33%. This prodrug is activated and converted to an active form, Pyrazinoic acid (POA), by Pyrazinamidase (PZase) enzyme. Mtb resistance to PZA is the outcome of mutations frequently reported in pncA, rpsA, and panD genes. Among the mentioned genes, pncA mutations contribute to 72-99% of the total resistance to PZA. Thus, considering the vital importance of this gene in PZA resistance, its frequent mutations (D49N, Y64S, W68G, and F94A) were investigated through in-depth computational techniques to put conclusions that might be useful for new scaffolds design or structure optimization to improve the efficacy of the available drugs. Mutants and wild type PZase were used in extensive and long-run molecular dynamics simulations in triplicate to disclose the resistance mechanism induced by the above-mentioned point mutations. Our analysis suggests that these mutations alter the internal dynamics of PZase and hinder the correct orientation of PZA to the enzyme. Consequently, the PZA has a low binding energy score with the mutants compared with the wild type PZase. These mutations were also reported to affect the binding of Fe2+ ion and its coordinated residues. Conformational dynamics also revealed that β-strand two is flipped, which is significant in Fe2+ binding. MM-GBSA analysis confirmed that these mutations significantly decreased the binding of PZA. In conclusion, these mutations cause conformation alterations and deformities that lead to PZA resistance.

Atypical Genetic Basis of Pyrazinamide Resistance in Monoresistant Mycobacterium tuberculosis

Pyrazinamide (PZA) is a widely used antitubercular chemotherapeutic. Typically, PZA resistance (PZA-R) emerges in Mycobacterium tuberculosis strains with existing resistance to isoniazid and rifampin (i.e., multidrug resistance [MDR]) and is conferred by loss-of-function pncA mutations that inhibit conversion to its active form, pyrazinoic acid (POA). PZA-R departing from this canonical scenario is poorly understood. Here, we genotyped pncA and purported alternative PZA-R genes (panD, rpsA, and clpC1) with long-read sequencing of 19 phenotypically PZA-monoresistant isolates collected in Sweden and compared their phylogenetic and genomic characteristics to a large set of MDR PZA-R (MDR_PZA-R) isolates. We report the first association of ClpC1 mutations with PZA-R in clinical isolates, in the ClpC1 promoter (clpC1p₋₁₃₈) and the N terminus of ClpC1 (ClpC1_Val63Ala). Mutations have emerged in both these regions under POA selection in vitro, and the N-terminal region of ClpC1 has been implicated further, through its POA-dependent efficacy in PanD proteolysis. ClpC1_Val63Ala mutants spanned 4 Indo-Oceanic sublineages. Indo-Oceanic isolates invariably harbored ClpC1_Val63Ala and were starkly overrepresented (odds ratio [OR] = 22.2, P < 0.00001) among PZA-monoresistant isolates (11/19) compared to MDR_PZA-R isolates (5/80). The genetic basis of Indo-Oceanic isolates’ overrepresentation in PZA-monoresistant tuberculosis (TB) remains undetermined, but substantial circumstantial evidence suggests that ClpC1_Val63Ala confers low-level PZA resistance. Our findings highlight ClpC1 as potentially clinically relevant for PZA-R and reinforce the importance of genetic background in the trajectory of resistance development.

Performance of Wayne assay for detection of pyrazinamide resistance in Mycobacterium tuberculosis: a meta-analysis study

Conventional culture-based drug susceptibility testing (DST) of Mycobacterium tuberculosis to pyrazinamide (PZA) is time-consuming and difficult to perform. The current systematic review and meta-analysis was aimed to evaluate the diagnostic accuracy of Wayne assay against culture-based DSTs as the reference standard. We searched the MEDLINE/Pubmed, Embase, and Web of Science databases for the relevant records. The QUADAS-2 tool was used to assess the quality of the studies. Diagnostic accuracy measures (i.e., sensitivity and specificity) were pooled with a random-effects model. Statistical analyses were performed with STATA (version 14, Stata Corporation, College Station, TX, USA), RevMan (version 5.3; The Nordic Cochrane Centre, the Cochrane Collaboration, Copenhagen, Denmark), and Meta-DiSc (version 1.4, Cochrane Colloquium, Barcelona, Spain). A total of 31 articles comprising data for 2457 isolates of M. tuberculosis were included in the final analysis. The pooled sensitivity and specificity of the Wayne assay against all reference tests (the combination of BACTEC MGIT 960, BACTEC 460, and proportion method) were 86.6% (95% CI: 84.3-88.7) and 96.0% (95% CI: 94.8-97). The positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the curve (AUC) estimates were found to be 17.6 (95% CI: 10.5-29.3), 0.11 (95% CI: 0.06-0.20), 164 (95% CI: 83-320) and 97%, respectively. Deek's test result indicated no evidence for publication bias (P > 0.05). Although the current study shows that the Wayne test is sensitive and specific for detecting PZA resistance, it may be used in combination with conventional DSTs to diagnose PZA resistance accurately.

Insight into the drug resistance whole genome of Mycobacterium tuberculosis isolates from Khyber Pakhtunkhwa, Pakistan

Whole genome sequencing (WGS) is one of the most reliable methods for detection of drug resistance, genetic diversity in other virulence factor and also evolutionary dynamics of Mycobacterium tuberculosis complex (MTBC). First-line anti-tuberculosis drugs are the major weapons against Mycobacterium tuberculosis (MTB). However, the emergence of drug resistance remained a major obstacle towards global tuberculosis (TB) control program 2030, especially in high burden countries including Pakistan. To overcome the resistance and design potent drugs, genomic variations in drugs targets as well as in the virulence and evolutionary factors might be useful for better understanding and designing potential inhibitors. Here we aimed to find genomic variations in the first-line drugs targets, along with other virulence and evolutionary factors among the circulating isolates in Khyber Pakhtunkhwa, Pakistan. Samples were collected and drug susceptibility testing (DST) was performed as per WHO standard. The resistance samples were subjected to WGS. Among the five whole genome sequences, three samples (NCBI BioProject Accession: PRJNA629298, PRJNA629388) harbored 1997, 1162, and 2053 mutations. Some novel mutations have been detected in drugs targets. Similarly, numerous novel variants have also been detected in virulency and evolutionary factors, PE, PPE, and secretory system of MTB isolates. Exploring the genomic variations among the circulating isolates in geographical specific locations might be useful for future drug designing. To the best of our knowledge, this is the first study that provides useful data regarding the insight genomic variations in virulency, evolutionary factors including ESX and PE/PPE as well as drug targets, for better understanding and management of TB in a WHO declared high burden country.

Computational modeling and bioinformatic analyses of functional mutations in drug target genes in Mycobacterium tuberculosis

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MycoTRAP-DB, a database of mutations and their impact on normal functionality of protein in M.tb genes.

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Several secondary mutations were identified with significant impact on protein structure and function.

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Comprehensive information gives insight for screening of suspected hotspots in advance to combat drug resistant TB.

Tuberculosis (TB) continues to be the leading cause of deaths due to its persistent drug resistance and the consequent ineffectiveness of anti-TB treatment. Recent years witnessed huge amount of sequencing data, revealing mutations responsible for drug resistance. However, the lack of an up-to-date repository remains a barrier towards utilization of these data and identifying major mutations-associated with resistance. Amongst all mutations, non-synonymous mutations alter the amino acid sequence of a protein and have a much greater effect on pathogenicity. Hence, this type of gene mutation is of prime interest of the present study. The purpose of this study is to develop an updated database comprising almost all reported substitutions within the Mycobacterium tuberculosis (M.tb) drug target genes rpoB, inhA, katG, pncA, gyrA and gyrB. Various bioinformatics prediction tools were used to assess the structural and biophysical impacts of the resistance causing non-synonymous single nucleotide polymorphisms (nsSNPs) at the molecular level. This was followed by evaluating the impact of these mutations on binding affinity of the drugs to target proteins. We have developed a comprehensive online resource named MycoTRAP-DB (Mycobacterium tuberculosis Resistance Associated Polymorphisms Database) that connects mutations in genes with their structural, functional and pathogenic implications on protein. This database is accessible at http://139.59.12.92. This integrated platform would enable comprehensive analysis and prioritization of SNPs for the development of improved diagnostics and antimycobacterial medications. Moreover, our study puts forward secondary mutations that can be important for prognostic assessments of drug-resistance mechanism and actionable anti-TB drugs.

Value of routine whole genome sequencing for Mycobacterium tuberculosis drug resistance detection

Routine whole genome sequencing (WGS) of pathogens is becoming more feasible as sequencing costs decrease and access to benchtop sequencing equipment and bioinformatics pipelines increases. This study examined the added value gained from implementing routine WGS of all Mycobacterium tuberculosis isolates in New South Wales, Australia. Drug resistance markers inferred from WGS data were compared to commercial genotypic drug susceptibility testing (DST) assays and conventional phenotypic DST in all isolates sequenced between 2016 and 2019. Of the 1107 clinical M. tuberculosis isolates sequenced, 29 (2.6%) were multi-drug resistant (MDR); most belonged to Beijing (336; 30.4%) or East-African Indian (332; 30%) lineages. Compared with conventional phenotypic DST, WGS identified an additional 1% of isolates which were likely drug resistant, explained by mutations previously associated with treatment failure and mixed bacterial populations. However, WGS provided a 20% increase in drug resistance detection in comparison with commercial genotypic assays by identifying mutations outside of the classic resistance determining regions in rpoB, inhA, katG, pncA and embB genes. Gains in drug resistance detection were significant (p = 0.0137, paired t-test), but varied substantially for different phylogenetic lineages. In low incidence settings, routine WGS of M. tuberculosis provides better guidance for person-centered management of drug resistant tuberculosis than commercial genotypic assays.

Deep amplicon sequencing for culture-free prediction of susceptibility or resistance to 13 anti-tuberculous drugs

Conventional molecular tests for detecting Mycobacterium tuberculosis complex (MTBC) drug resistance on clinical samples cover a limited set of mutations. Whole-genome sequencing (WGS) typically requires culture.

Here, we evaluated the Deeplex Myc-TB targeted deep-sequencing assay for prediction of resistance to 13 anti-tuberculous drugs/drug classes, directly applicable on sputum.

With MTBC DNA tests, the limit of detection was 100–1000 genome copies for fixed resistance mutations. Deeplex Myc-TB captured in silico 97.1–99.3% of resistance phenotypes correctly predicted by WGS from 3651 MTBC genomes. On 429 isolates, the assay predicted 92.2% of 2369 first- and second-line phenotypes, with a sensitivity of 95.3% and a specificity of 97.4%. 56 out of 69 (81.2%) residual discrepancies with phenotypic results involved pyrazinamide, ethambutol and ethionamide, and low-level rifampicin or isoniazid resistance mutations, all notoriously prone to phenotypic testing variability. Only two out of 91 (2.2%) resistance phenotypes undetected by Deeplex Myc-TB had known resistance-associated mutations by WGS analysis outside Deeplex Myc-TB targets. Phenotype predictions from Deeplex Myc-TB analysis directly on 109 sputa from a Djibouti survey matched those of MTBSeq/PhyResSE/Mykrobe, fed with WGS data from subsequent cultures, with a sensitivity of 93.5/98.5/93.1% and a specificity of 98.5/97.2/95.3%, respectively. Most residual discordances involved gene deletions/indels and 3–12% heteroresistant calls undetected by WGS analysis or natural pyrazinamide resistance of globally rare “Mycobacterium canettii” strains then unreported by Deeplex Myc-TB. On 1494 arduous sputa from a Democratic Republic of the Congo survey, 14 902 out of 19 422 (76.7%) possible susceptible or resistance phenotypes could be predicted culture-free.

Deeplex Myc-TB may enable fast, tailored tuberculosis treatment.

The novel Deeplex Myc-TB molecular assay shows a high degree of accuracy for extensive prediction of susceptibility and resistance to 13 anti-tuberculous drugs, directly achievable without culture, which may enable fast, tailored tuberculosis treatmenthttps://bit.ly/3bAvcAt

Refining MDR-TB treatment regimens for ultra short therapy (TB-TRUST): study protocol for a randomized controlled trial

Background

Multidrug-resistant tuberculosis (MDR-TB) are unsatisfied to treat, pressing more effective and innovative treatment regimens. New efficient regimens for MDR-TB have obtained high treatment success rates. However, those regimens without drug susceptibility testing (DST) are also likely to contribute to the emergence of resistance. Precision treatments guided by DST might optimize the patients’ treatment outcome individually and minimize resistance amplification.

Methods

TB-TRUST is a phase III, multicenter, open-label, randomized controlled clinical trial of non-inferiority comparing the treatment success rate between the World Health Organization (WHO) shorter regimen and the refined ultra-short regimen for fluoroquinolones and second-line injectable drugs susceptible rifampicin-resistant TB. The control arm uses the WHO injectable-containing shorter regimen for 36–44 weeks depending on time of sputum smear conversion. The investigational arm uses a refined ultra-short regimen guided by molecular DST to pyrazinamide via whole-genome sequencing (WGS) to optimize the treatment of pyrazinamide-susceptible patients with levofloxacin, linezolid, cycloserine and pyrazinamide for 24–32 weeks and pyrazinamide-resistant with levofloxacin, linezolid, cycloserine and clofazimine for 36–44 weeks. The primary outcome is the treatment success rate without relapse at 84 weeks after treatment initiation. Secondary outcomes include the time of sputum culture conversion and occurrence of adverse events. Assuming α = 0.025 level of significance (one-sided test), a power of 80%, a < 10% difference in treatment success rate between control arm and investigational (80% vs. 82%), and a 5% lost follow-up rate, the number of participants per arm to show non-inferiority was calculated as 177(354 in total).

Discussion

Rapid molecular testing distinguishes patients who are eligible for shorter regimen with fluoroquinolone and the WGS-guided results shorten the treatment to 6 months for pyrazinamide susceptible patients. It’s foreseeable that not only novel developed medicines, but also traditional powerful medicines with the susceptibility confirmed by DST are the key factors to ensure the effect of anti-MDR-TB drugs. As a DST-guided precision treatment, TB-TRUST are expected to optimize therapy outcome in more patients who cannot afford the expensive new medicines and minimize and even avoid resistance amplification with the rational use of anti-TB drugs.

Trail registration

ClinicalTrial.gov, NCT03867136. Registered on March 7, 2019.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05870-w.

Genomic Variations in Drug Resistant Mycobacterium tuberculosis Strains Collected from Patients with Different Localization of Infection

Mycobacterium tuberculosis is a highly studied pathogen due to public health importance. Despite this, problems like early drug resistance, diagnostics and treatment success prediction are still not fully resolved. Here, we analyze the incidence of point mutations widely used for drug resistance detection in laboratory practice and conduct comparative analysis of whole-genome sequence (WGS) for clinical M. tuberculosis strains collected from patients with pulmonary tuberculosis (PTB) and extra-pulmonary tuberculosis (XPTB) localization. A total of 72 pulmonary and 73 extrapulmonary microbiologically characterized M. tuberculosis isolates were collected from patients from 2007 to 2014 in Russia. Genomic DNA was used for WGS and obtained data allowed identifying major mutations known to be associated with drug resistance to first-line and second-line antituberculous drugs. In some cases previously described mutations were not identified. Using genome-based phylogenetic analysis we identified M. tuberculosis substrains associated with distinctions in the occurrence in PTB vs. XPTB cases. Phylogenetic analyses did reveal M. tuberculosis genetic substrains associated with TB localization. XPTB was associated with Beijing sublineages Central Asia (Beijing CAO), Central Asia Clade A (Beijing A) and 4.8 groups, while PTB localization was associated with group LAM (4.3). Further, the XPTB strain in some cases showed elevated drug resistance patterns relative to PTB isolates. HIV was significantly associated with the development of XPTB in the Beijing B0/W148 group and among unclustered Beijing isolates.

Mutations in fbiD (Rv2983) as a Novel Determinant of Resistance to Pretomanid and Delamanid in Mycobacterium tuberculosis

The nitroimidazole prodrugs delamanid and pretomanid comprise one of only two new antimicrobial classes approved to treat tuberculosis (TB) in 50 years. Prior in vitro studies suggest a relatively low barrier to nitroimidazole resistance in Mycobacterium tuberculosis, but clinical evidence is limited to date. We selected pretomanid-resistant M. tuberculosis mutants in two mouse models of TB using a range of pretomanid doses. The frequency of spontaneous resistance was approximately 10^-5 CFU. Whole-genome sequencing of 161 resistant isolates from 47 mice revealed 99 unique mutations, of which 91% occurred in 1 of 5 genes previously associated with nitroimidazole activation and resistance, namely, fbiC (56%), fbiA (15%), ddn (12%), fgd (4%), and fbiB (4%). Nearly all mutations were unique to a single mouse and not previously identified. The remaining 9% of resistant mutants harbored mutations in Rv2983 (fbiD), a gene not previously associated with nitroimidazole resistance but recently shown to be a guanylyltransferase necessary for cofactor F₄₂₀ synthesis. Most mutants exhibited high-level resistance to pretomanid and delamanid, although Rv2983 and fbiB mutants exhibited high-level pretomanid resistance but relatively small changes in delamanid susceptibility. Complementing an Rv2983 mutant with wild-type Rv2983 restored susceptibility to pretomanid and delamanid. By quantifying intracellular F₄₂₀ and its precursor Fo in overexpressing and loss-of-function mutants, we provide further evidence that Rv2983 is necessary for F₄₂₀ biosynthesis. Finally, Rv2983 mutants and other F₄₂₀H₂-deficient mutants displayed hypersusceptibility to some antibiotics and to concentrations of malachite green found in solid media used to isolate and propagate mycobacteria from clinical samples.

Vitamin in the Crosshairs: Targeting Pantothenate and Coenzyme A Biosynthesis for New Antituberculosis Agents

Despite decades of dedicated research, there remains a dire need for new drugs against tuberculosis (TB). Current therapies are generations old and problematic. Resistance to these existing therapies results in an ever-increasing burden of patients with disease that is difficult or impossible to treat. Novel chemical entities with new mechanisms of action are therefore earnestly required. The biosynthesis of coenzyme A (CoA) has long been known to be essential in Mycobacterium tuberculosis (Mtb), the causative agent of TB. The pathway has been genetically validated by seminal studies in vitro and in vivo. In Mtb, the CoA biosynthetic pathway is comprised of nine enzymes: four to synthesize pantothenate (Pan) from l-aspartate and α-ketoisovalerate; five to synthesize CoA from Pan and pantetheine (PantSH). This review gathers literature reports on the structure/mechanism, inhibitors, and vulnerability of each enzyme in the CoA pathway. In addition to traditional inhibition of a single enzyme, the CoA pathway offers an antimetabolite strategy as a promising alternative. In this review, we provide our assessment of what appear to be the best targets, and, thus, which CoA pathway enzymes present the best opportunities for antitubercular drug discovery moving forward.

Nonredundant functions of Mycobacterium tuberculosis chaperones promote survival under stress

Bacterial chaperones ClpB and DnaK, homologs of the respective eukaryotic heat shock proteins Hsp104 and Hsp70, are essential in the reactivation of toxic protein aggregates that occur during translation or periods of stress. In the pathogen Mycobacterium tuberculosis (Mtb), the protective effect of chaperones extends to survival in the presence of host stresses, such as protein-damaging oxidants. However, we lack a full understanding of the interplay of Hsps and other stress response genes in mycobacteria. Here, we employ genome-wide transposon mutagenesis to identify the genes that support clpB function in Mtb. In addition to validating the role of ClpB in Mtb's response to oxidants, we show that HtpG, a homolog of Hsp90, plays a distinct role from ClpB in the proteotoxic stress response. While loss of neither clpB nor htpG is lethal to the cell, loss of both through genetic depletion or small molecule inhibition impairs recovery after exposure to host-like stresses, especially reactive nitrogen species. Moreover, defects in cells lacking clpB can be complemented by overexpression of other chaperones, demonstrating that Mtb's stress response network depends upon finely tuned chaperone expression levels. These results suggest that inhibition of multiple chaperones could work in concert with host immunity to disable Mtb.

Mechanistic analysis of A46V, H57Y, and D129N in pyrazinamidase associated with pyrazinamide resistance

Pyrazinamide (PZA) is a component of first-line drugs, active against latent Mycobacterium tuberculosis (MTB) isolates. The prodrug is activated into the active form, pyrazinoic acid (POA) via pncA gene-encoded pyrazinamidase (PZase). Mutations in pncA have been reported, most commonly responsible for PZA-resistance in more than 70% of the resistant cases. In our previous study, we detected many mutations in PZase among PZA-resistance MTB isolates including A46V, H71Y, and D129N. The current study was aimed to investigate the molecular mechanism of PZA-resistance behind mutants (MTs) A46V, H71Y, and D129N in comparison with the wild type (WT) through molecular dynamic (MD) simulation. MTB positive samples were subjected to PZA drug susceptibility testing (DST) against critical concentration (100ug/ml). The resistant samples were subjected to pncA sequencing. Thirty-six various mutations have been observed in the coding region of pncA of PZA-resistant isolates (GenBank accession No. MH461111) including A46V, H71Y, and D129N. The post-simulation analysis revealed a significant variation in MTs structural dynamics as compared to the WT. Root means square deviations (RMSD) and Root means square fluctuation (RMSF) has been found in variation between WT and MTs. Folding effect and pocket volume were altered in MTs when compared with WT. Geometric matching supports the effect of mutation A46V, H71Y, and D129N on PZase structure that may have an insight effect on PZase dynamics, making them vulnerable to convert pro-PZA into active form, POA. In conclusion, the current analyses will provide useful information behind PZA-resistance for better management of drug-resistant TB.

Pyrazinamide resistance of novel mutations in pncA and their dynamic behavior

Pyrazinamide (PZA) is one of the essential anti-mycobacterium drugs, active against non-replicating Mycobacterium tuberculosis (MTB) isolates. PZA is converted into its active state, called pyrazinoic acid (POA), by action of pncA encoding pyrazinamidase (PZase). In the majority of PZA-resistance isolates, pncA harbored mutations in the coding region. In our recent report, we detected a number of novel variants in PZA-resistance (PZA^R) MTB isolates, whose resistance mechanisms were yet to be determined. Here we performed several analyses to unveil the PZA^R mechanism of R123P, T76P, G150A, and H71R mutants (MTs) through molecular dynamics (MD) simulations. In brief, culture positive MTB isolates were subjected to PZA susceptibility tests using the WHO recommended concentration of PZA (100 μg ml⁻¹). The PZA^R samples were screened for mutations in pncA along sensitive isolates through polymerase chain reactions and sequencing. A large number of variants (GeneBank accession no. MH461111), including R123P, T76P, G150A, and H71R, have been spotted in more than 70% of isolates. However, the mechanism of PZA^R for mutants (MTs) R123P, T76P, G150A, and H71R was unknown. For the MTs and native PZase structures (WT), thermodynamic properties were compared using molecular dynamics simulations for 100 ns. The MTs structural activity was compared to the WT. Folding effect and pocket volume variations have been detected when comparing between WT and MTs. Geometric matching further confirmed the effect of R123P, T76P, G150A, and H71R mutations on PZase dynamics, making them vulnerable for activating the pro-drug into POA. This study offers a better understanding for management of PZA^R TB. The results may be used as alternative diagnostic tools to infer PZA resistance at a structural dynamics level.

We performed several analyses to unveil the pyrazinamide-resistance mechanism of R123P, T76P, G150A, and H71R mutants through molecular dynamics simulations.

How To Optimally Combine Genotypic and Phenotypic Drug Susceptibility Testing Methods for Pyrazinamide

False-susceptible phenotypic drug-susceptibility testing (DST) results for pyrazinamide due to mutations with MICs close to the critical concentration (CC) confound the classification of pncA resistance mutations, leading to an underestimate of the specificity of genotypic DST. This could be minimized by basing treatment decisions on well-understood mutations and by adopting an area of technical uncertainty for phenotypic DST rather than only testing the CC, as is current practice for the Mycobacterium tuberculosis complex.

Exploiting Homoplasy in Genome-Wide Association Studies to Enhance Identification of Antibiotic-Resistance Mutations in Bacterial Genomes

Many antibacterial drugs have multiple mechanisms of resistance, which are often represented simultaneously by a mixture of resistance mutations (some more frequent than others) in a clinical population. This presents a challenge for Genome-Wide Association Studies (GWAS) methods, making it difficult to detect less prevalent resistance mechanisms purely through (weak) statistical associations. Homoplasy, or the occurrence of multiple independent mutations at the same site, is often observed with drug resistance mutations and can be a strong indicator of positive selection. However, traditional GWAS methods, such as those based on allele counting or linear regression, are not designed to take homoplasy into account. In this article, we present a new method, called ECAT (for Evolutionary Cluster-based Association Test), that extends traditional regression-based GWAS methods with the ability to take advantage of homoplasy. This is achieved through a preprocessing step which identifies hypervariable regions in the genome exhibiting statistically significant clusters of distinct evolutionary changes, to which association testing by a linear mixed model (LMM) is applied using GEMMA (a well-established LMM-based GWAS tool). Thus, the approach can be viewed as extending GEMMA from the usual site- or gene-level analysis to focusing on clustered regions of mutations. This approach was evaluated on a large collection of more than 600 clinical isolates of multidrug-resistant (MDR) Mycobacterium tuberculosis from Lima, Peru. We show that ECAT does a better job of detecting known resistance mutations for several antitubercular drugs (including less prevalent mutations with weaker associations), compared with (site- or gene-based) GEMMA, as representative of existing GWAS methods. The power of the multiphase approach in ECAT comes from focusing association testing on the hypervariable regions of the genome, which reduces complexity in the model and increases statistical power.

Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors

BACKGROUND

Pyrazinamide is an important drug against the latent stage of tuberculosis and is used in both first- and second-line treatment regimens. Pyrazinamide-susceptibility test usually takes a week to have a diagnosis to guide initial therapy, implying a delay in receiving appropriate therapy. The continued increase in multi-drug resistant tuberculosis and the prevalence of pyrazinamide resistance in several countries makes the development of assays for prompt identification of resistance necessary. The main cause of pyrazinamide resistance is the impairment of pyrazinamidase function attributed to mutations in the promoter and/or pncA coding gene. However, not all pncA mutations necessarily affect the pyrazinamidase function.

OBJECTIVE

To develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene.

METHODS

We measured the catalytic constant (kcat), KM, enzymatic efficiency, and enzymatic activity of 35 recombinant mutated pyrazinamidase and the wild type (Protein Data Bank ID = 3pl1). From all the 3D modeled structures, we extracted several predictors based on three categories: structural stability (estimated by normal mode analysis and molecular dynamics), physicochemical, and geometrical characteristics. We used a stepwise Akaike's information criterion forward multiple log-linear regression to model each kinetic parameter with each category of predictors. We also developed weighted models combining the three categories of predictive models for each kinetic parameter. We tested the robustness of the predictive ability of each model by 6-fold cross-validation against random models.

RESULTS

The stability, physicochemical, and geometrical descriptors explained most of the variability (R2) of the kinetic parameters. Our models are best suited to predict kcat, efficiency, and activity based on the root-mean-square error of prediction of the 6-fold cross-validation.

CONCLUSIONS

This study shows a quick approach to predict the pyrazinamidase function only from the pncA sequence when point mutations are present. This can be an important tool to detect pyrazinamide resistance.

Targeted-Sequencing Workflows for Comprehensive Drug Resistance Profiling of Mycobacterium tuberculosis Cultures Using Two Commercial Sequencing Platforms: Comparison of Analytical and Diagnostic Performance, Turnaround Time, and Cost

Background

The emergence of Mycobacterium tuberculosis with complex drug resistance profiles necessitates a rapid and comprehensive drug susceptibility test for guidance of patient treatment. We developed two targeted-sequencing workflows based on Illumina MiSeq and Nanopore MinION for the prediction of drug resistance in M. tuberculosis toward 12 antibiotics.

Methods

A total of 163 M. tuberculosis isolates collected from Hong Kong and Ethiopia were subjected to a multiplex PCR for simultaneous amplification of 19 drug resistance-associated genetic regions. The amplicons were then barcoded and sequenced in parallel on MiSeq and MinION in respective batch sizes of 24 and 12 samples. A web-based bioinformatics pipeline, BacterioChek-TB, was developed to translate the raw datasets into clinician-friendly reports.

Results

Both platforms successfully sequenced all samples with mean read depths of 1,127× and 1,649×, respectively. The variant calling by MiSeq and MinION could achieve 100% agreement if variants with an allele frequency of &lt;40% reported by MinION were excluded. Both workflows achieved a mean clinical sensitivity of 94.8% and clinical specificity of 98.0% when compared with phenotypic drug susceptibility test (pDST). Turnaround times for the MiSeq and MinION workflows were 38 and 15 h, facilitating the delivery of treatment guidance at least 17–18 days earlier than pDST, respectively. The higher cost per sample on the MinION platform ($71.56) versus the MiSeq platform ($67.83) was attributed to differences in batching capabilities.

Conclusion

Our study demonstrates the interchangeability of MiSeq and MinION platforms for generation of accurate and actionable results for the treatment of tuberculosis.

Direct Determination of Pyrazinamide (PZA) Susceptibility by Sputum Microscopic Observation Drug Susceptibility (MODS) Culture at Neutral pH: the MODS-PZA Assay

Pyrazinamide (PZA) is considered the pivot drug in all tuberculosis treatment regimens due to its particular action on the persistent forms of Mycobacterium tuberculosis. However, no drug susceptibility test (DST) is considered sufficiently reliable for routine application. Although molecular tests are endorsed, their application is limited to known PZA resistance associated mutations. Microbiological DSTs for PZA have been restricted by technical limitations, especially the necessity for an acidic pH.

Pyrazinamide (PZA) is considered the pivot drug in all tuberculosis treatment regimens due to its particular action on the persistent forms of Mycobacterium tuberculosis. However, no drug susceptibility test (DST) is considered sufficiently reliable for routine application. Although molecular tests are endorsed, their application is limited to known PZA resistance associated mutations. Microbiological DSTs for PZA have been restricted by technical limitations, especially the necessity for an acidic pH. Here, for the first time, MODS culture at neutral pH was evaluated using high PZA concentrations (400 and 800 μg/ml) to determine PZA susceptibility directly from sputum samples. Sputum samples were cultured with PZA for up to 21 days at 37°C. Plate reading was performed at two time points: R1 (mean, 10 days) and R2 (mean, 13 days) for each PZA concentration. A consensus reference test, composed of MGIT-PZA, pncA sequencing, and the classic Wayne test, was used. A total of 182 samples were evaluated. The sensitivity and specificity for 400 μg/ml ranged from 76.9 to 89.7 and from 93.0 to 97.9%, respectively, and for 800 μg/ml ranged from 71.8 to 82.1 and from 95.8 to 98.6%, respectively. Compared to MGIT-PZA, our test showed a similar turnaround time (medians of 10 and 12 days for PZA-sensitive and -resistant isolates, respectively). In conclusion, MODS-PZA is presented as a fast, simple, and low-cost DST that could complement the MODS assay to evaluate resistance to the principal first-line antituberculosis drugs. Further optimization of test conditions would be useful in order to increase its performance.

Gibbs Free Energy Calculation of Mutation in PncA and RpsA Associated With Pyrazinamide Resistance

A central approach for better understanding the forces involved in maintaining protein structures is to investigate the protein folding and thermodynamic properties. The effect of the folding process is often disturbed in mutated states. To explore the dynamic properties behind mutations, molecular dynamic (MD) simulations have been widely performed, especially in unveiling the mechanism of drug failure behind mutation. When comparing wild type (WT) and mutants (MTs), the structural changes along with solvation free energy (SFE), and Gibbs free energy (GFE) are calculated after the MD simulation, to measure the effect of mutations on protein structure. Pyrazinamide (PZA) is one of the first-line drugs, effective against latent Mycobacterium tuberculosis isolates, affecting the global TB control program 2030. Resistance to this drug emerges due to mutations in pncA and rpsA genes, encoding pyrazinamidase (PZase) and ribosomal protein S1 (RpsA) respectively. The question of how the GFE may be a measure of PZase and RpsA stabilities, has been addressed in the current review. The GFE and SFE of MTs have been compared with WT, which were already found to be PZA-resistant. WT structures attained a more stable state in comparison with MTs. The physiological effect of a mutation in PZase and RpsA may be due to the difference in energies. This difference between WT and MTs, depicted through GFE plots, might be useful in predicting the stability and PZA-resistance behind mutation. This study provides useful information for better management of drug resistance, to control the global TB problem.

Rapid Pyrazinamide Drug Susceptibility Testing using a Closed-Tube PCR Assay of the Entire pncA gene

The continued use of pyrazinamide in the treatment of tuberculosis in the absence of a rapid, accurate and standardized pyrazinamide drug susceptibility assays is of great concern. While whole genome sequencing holds promise, it is not yet feasible option in low resource settings as it requires expensive instruments and bioinformatic analysis. We investigated the diagnostic performance of a closed-tube Linear-After-The-Exponential (LATE)-PCR assay for pyrazinamide susceptibility in Mycobacterium tuberculosis. Based on a set of 654 clinical Mycobacterium tuberculosis culture isolates with known mutations throughout the pncA gene as determined by Sanger sequencing, the assay displays excellent sensitivity of 96.9% (95% CI: 95.2-98.6) and specificity of 97.9% (95% CI: 96.1-99.7). In a subset of 384 isolates with phenotypic drug susceptibility testing, we also observed high sensitivity of 98.9% (95% CI: 97.5-100) but lower specificity of 91.8% (95% CI: 87.9-95.8) when compared to phenotypic drug susceptibility testing. We conclude that the LATE PCR assay offers both a rapid and accurate prediction of pyrazinamide susceptibility.

The Bewildering Antitubercular Action of Pyrazinamide

Pyrazinamide (PZA) is a cornerstone antimicrobial drug used exclusively for the treatment of tuberculosis (TB). Due to its ability to shorten drug therapy by 3 months and reduce disease relapse rates, PZA is considered an irreplaceable component of standard first-line short-course therapy for drug-susceptible TB and second-line treatment regimens for multidrug-resistant TB. Despite over 60 years of research on PZA and its crucial role in current and future TB treatment regimens, the mode of action of this unique drug remains unclear. Defining the mode of action for PZA will open new avenues for rational design of novel therapeutic approaches for the treatment of TB. In this review, we discuss the four prevailing models for PZA action, recent developments in modulation of PZA susceptibility and resistance, and outlooks for future research and drug development.

Structure guided prediction of Pyrazinamide resistance mutations in pncA

Pyrazinamide plays an important role in tuberculosis treatment; however, its use is complicated by side-effects and challenges with reliable drug susceptibility testing. Resistance to pyrazinamide is largely driven by mutations in pyrazinamidase (pncA), responsible for drug activation, but genetic heterogeneity has hindered development of a molecular diagnostic test. We proposed to use information on how variants were likely to affect the 3D structure of pncA to identify variants likely to lead to pyrazinamide resistance. We curated 610 pncA mutations with high confidence experimental and clinical information on pyrazinamide susceptibility. The molecular consequences of each mutation on protein stability, conformation, and interactions were computationally assessed using our comprehensive suite of graph-based signature methods, mCSM. The molecular consequences of the variants were used to train a classifier with an accuracy of 80%. Our model was tested against internationally curated clinical datasets, achieving up to 85% accuracy. Screening of 600 Victorian clinical isolates identified a set of previously unreported variants, which our model had a 71% agreement with drug susceptibility testing. Here, we have shown the 3D structure of pncA can be used to accurately identify pyrazinamide resistance mutations. SUSPECT-PZA is freely available at: http://biosig.unimelb.edu.au/suspect_pza/.

Detection of Novel Gene Mutations Associated with Pyrazinamide Resistance in Multidrug-Resistant Mycobacterium tuberculosis Clinical Isolates in Southern China

Objective

Pyrazinamide (PZA) is a cornerstone of modern tuberculosis regimens. This study aimed to investigate the performance of genotypic testing of pncA ⁺ upstream region, rpsA, panD, Rv2783c, and clpC1 genes to add insights for more accurate molecular diagnosis of PZA-resistant (R) Mycobacterium tuberculosis.

Methods

Drug susceptibility testing, sequencing analysis of PZA-related genes including the entire operon of pncA (Rv2044c-pncA-Rv2042c) and PZase assay were performed for 448 M. tuberculosis clinical isolates.

Results

Our data showed that among 448 M. tuberculosis clinical isolates, 113 were MDR, 195 pre-XDR and 70 XDR TB, while the remaining 70 strains had other combinations of drug-resistance. A total of 60.04% (269/448) M. tuberculosis clinical isolates were resistant to PZA, of which 78/113 were MDR, 119/195 pre-XDR and 29/70 XDR TB strains. PZA^R isolates have predominance (83.3%) of Beijing genotype. Genotypic characterization of Rv2044c-pncA-Rv2042c revealed novel nonsynonymous mutations in Rv2044c with negative PZase activity which led to confer PZA^R. Compared with phenotypic data, 84.38% (227/269) PZA^R strains with mutations in pncA ⁺ upstream region exhibited 83.64% sensitivity but the combined evaluation of the mutations in rpsA 2.60% (7/269), panD 1.48% (4/269), Rv2783c 1.11% (3/269) and Rv2044c 0.74% (2/269) increased the sensitivity to 89.59%. Fifty-seven novel mutations were identified in this study. Interestingly, a frameshift deletion (C-114del) in upstream of pncA^wt nullified the effect of A-11G mutation and induced positive PZase activity, divergent from five PZase negative A-11G PZA^R mutants. Twenty-six PZA^R strains having wild-type-sequenced genes with positive or negative PZase suggest the existence of unknown resistance mechanisms.

Conclusion

Our study revealed that PZA^R rate in MDR and pre-XDR TB was markedly higher in southern China. The concomitant evaluation of pncA ⁺ UFR, rpsA, panD, Rv2783c, and Rv2044c provides more dependable genotypic results of PZA resistance. Fifty-seven novel mutations/indels in this study may play a vital role as diagnostic markers. The upstream region of pncA and PZase regulation are valuable to explore the unknown mechanism of PZA-resistance.

Structural Dynamics Behind Clinical Mutants of PncA-Asp12Ala, Pro54Leu, and His57Pro of Mycobacterium tuberculosis Associated With Pyrazinamide Resistance

Pyrazinamide (PZA) is one of the main FDA approved drugs to be used as the first line of defense against Mycobacterium Tuberculosis (MTB). It is activated into pyrazinoic acid (POA) via MTB's pncA gene-encoded pyrazinamidase (PZase). Mutations are most commonly responsible for PZA-resistance in nearly 70% of the resistant samples. In the present work, MTB positive samples were chosen for PZA drug susceptibility testing (DST) against critical concentration (100 ug/ml) of PZA. The resistant samples were subjected to pncA sequencing. As a result, 36 various mutations have been observed in the PZA resistant samples, uploaded to the NCBI (GeneBank accession no. MH461111). Here we report the mechanism of PZA resistance behind the three mutants (MTs), Asp12Ala, Pro54Leu, and His57Pro in comparison with the wild type (WT) through molecular dynamics simulation to unveil how these mutations affect the overall conformational stability. The post-simulation analyses revealed notable deviations as compared to the WT structure. Molecular docking studies of PZA with MTs and WT, pocket volume inspection and overall shape complementarity analysis confirmed the deleterious nature of these mutations and gave an insight into the mechanism behind PZA-resistance. These analyses provide vital information regarding MTB drug resistance and could be extremely useful in therapy management and overcoming its global burden.

Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe

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.