Mycobacterium tuberculosis mutation rate estimates from different lineages predict substantial differences in the emergence of drug-resistant tuberculosis

Delineating the evolutionary pathway to multidrug-resistant outbreaks of a Mycobacterium tuberculosis L4.1.2.1/Haarlem sublineage

OBJECTIVES

We sought to capture the evolutionary itinerary of the Mycobacterium tuberculosis L4.1.2.1/Haarlem sublineage in northern Tunisia, where it caused a major multidrug-resistant (MDR) tuberculosis outbreak in a context strictly negative for HIV infection.

METHODS

We combined whole genome sequencing and Bayesian approaches using a representative collection of drug-susceptible and drug-resistant L4.1.2.1/Haarlem clinical strains (n = 121) recovered from the outbreak region over 16 years.

RESULTS

In the absence of drug resistance, the L4.1.2.1/Haarlem sublineage showed a propensity for rapid transmission as witnessed by the high clustering (44.6%) and recent transmission rates (25%), as well as the reduced mean distance between genome pairs. The entire pool of L4.1.2.1/Haarlem MDR strains was found to be linked to either the aforementioned major outbreak (68 individuals, 2001-2016) or to a minor, newly uncovered outbreak (six cases, 2001-2011). Strikingly, the two outbreaks descended independently from a common ancestor that can be dated back to 1886.

CONCLUSIONS

Our data point to the intrinsic propensity for rapid transmission of the M. tuberculosis L4.1.2.1/Haarlem sublineage in northern Tunisia, linking the overall MDR tuberculosis epidemic to a single ancestor. These findings bring out the important role of the bacillus' genetic background in the emergence of successful MDR M. tuberculosis clones.

Mycobacterium tuberculosis Beijing in the State of Nuevo Leon, Mexico

Tuberculosis remains a serious threat to human health as an infectious disease in Mexico. Data about the genotypes of circulating Mycobacterium tuberculosis isolates (MTB) in the State of Nuevo Leon, Mexico are scarce. We aimed to determine the genotypes of circulating MTB belonging to the Beijing lineage recovered from patients in the State of Nuevo Leon, Mexico. A total of 406 MTB isolates from this state were genotyped using the spoligotyping method and 18-locus MIRU-VNTR. Lineage classification and MTB transmission analysis were performed. Based on the spoligotyping analysis, we found 24 strains belonging to the Beijing genotype that were characterized phylogenetically. The MIRUs showed greater discriminatory power than the standard RFLP-IS6110 method; therefore, the greatest allelic diversity among the Beijing strains was observed with MIRU10, MIRU31, MIRU39, MRU40, and MIRU 26. MVLA analysis showed a profile variation between Beijing and non-Beijing strains. The minimum spanning tree (MST) showed that 79% (19) of the strains are related. All Beijing strains exhibited the deletion of region TbD1, which is a characteristic of modern strains. The application of spoligotyping and MIRU-VNTR-18 methods together proved to be more sensitive, discriminatory, and rapid than the standard method for the epidemiological analysis of Mycobacterium Beijing isolates. This study is one of the first to describe the genomic diversity of M. Beijing in the State of Nuevo Leon, Mexico.

Genetic Characterization and Population Structure of Drug-Resistant Mycobacterium tuberculosis Isolated from Brazilian Patients Using Whole-Genome Sequencing

The present study aimed to determine the genetic diversity of isolates of Mycobacterium tuberculosis (Mtb) from presumed drug-resistant tuberculosis patients from several states of Brazil. The isolates had been submitted to conventional drug susceptibility testing for first- and second-line drugs. Multidrug-resistant (MDR-TB) (54.8%) was the most frequent phenotypic resistance profile, in addition to an important high frequency of pre-extensive resistance (p-XDR-TB) (9.2%). Using whole-genome sequencing (WGS), we characterized 298 Mtb isolates from Brazil. Besides the analysis of genotype distribution and possible correlations between molecular and clinical data, we determined the performance of an in-house WGS pipeline with other online pipelines for Mtb lineages and drug resistance profile definitions. Sub-lineage 4.3 (52%) was the most frequent genotype, and the genomic approach revealed a p-XDR-TB level of 22.5%. We detected twenty novel mutations in three resistance genes, and six of these were observed in eight phenotypically resistant isolates. A cluster analysis of 170 isolates showed that 43.5% of the TB patients belonged to 24 genomic clusters, suggesting considerable ongoing transmission of DR-TB, including two interstate transmissions. The in-house WGS pipeline showed the best overall performance in drug resistance prediction, presenting the best accuracy values for five of the nine drugs tested. Significant associations were observed between suffering from fatal disease and genotypic p-XDR-TB (p = 0.03) and either phenotypic (p = 0.006) or genotypic (p = 0.0007) ethambutol resistance. The use of WGS analysis improved our understanding of the population structure of MTBC in Brazil and the genetic and clinical data correlations and demonstrated its utility for surveillance efforts regarding the spread of DR-TB, hopefully helping to avoid the emergence of even more resistant strains and to reduce TB incidence and mortality rates.

Actionable mechanisms of drug tolerance and resistance in Mycobacterium tuberculosis

The emergence of antimicrobial resistance (AMR) across bacterial pathogens presents a serious threat to global health. This threat is further exacerbated in tuberculosis (TB), mainly due to a protracted treatment regimen involving a combination of drugs. A diversity of factors contributes to the emergence of drug resistance in TB, which is caused by the pathogen Mycobacterium tuberculosis (Mtb). While the traditional genetic mutation-driven drug resistance mechanisms operate in Mtb, there are also several additional unique features of drug resistance in this pathogen. Research in the past decade has enriched our understanding of such unconventional factors as efflux pumps, bacterial heterogeneity, metabolic states, and host microenvironment. Given that the discovery of new antibiotics is outpaced by the emergence of drug resistance patterns displayed by the pathogen, newer strategies for combating drug resistance are desperately needed. In the context of TB, such approaches include targeting the efflux capability of the pathogen, modulating the host environment to prevent bacterial drug tolerance, and activating the host anti-mycobacterial pathways. In this review, we discuss the traditional mechanisms of drug resistance in Mtb, newer understandings and the shaping of a set of unconventional approaches to target both the emergence and treatment of drug resistance in TB.

The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova

The projected trajectory of multidrug resistant tuberculosis (MDR-TB) epidemics depends on the reproductive fitness of circulating strains of MDR M. tuberculosis (Mtb). Previous efforts to characterize the fitness of MDR Mtb have found that Mtb strains of the Beijing sublineage (Lineage 2.2.1) may be more prone to develop resistance and retain fitness in the presence of resistance-conferring mutations than other lineages. Using Mtb genome sequences from all culture-positive cases collected over two years in Moldova, we estimate the fitness of Ural (Lineage 4.2) and Beijing strains, the two lineages in which MDR is concentrated in the country. We estimate that the fitness of MDR Ural strains substantially exceeds that of other susceptible and MDR strains, and we identify several mutations specific to these MDR Ural strains. Our findings suggest that MDR Ural Mtb has been transmitting efficiently in Moldova and poses a substantial risk of spreading further in the region.

Prevalence, drug resistance, and genotypic diversity of the RDRio subfamily of Mycobacterium tuberculosis in Ecuador: a retrospective analysis for years 2012-2016

Introduction

A major sublineage within the Mycobacterium tuberculosis (MTB) LAM family characterized by a new in-frame fusion gene Rv3346c/55c was discovered in Rio de Janeiro (Brazil) in 2007, called RDRio, associated to drug resistance. The few studies about prevalence of MTB RDRio strains in Latin America reported values ranging from 3% in Chile to 69.8% in Venezuela, although no information is available for countries like Ecuador.

Methods

A total of 814 MTB isolates from years 2012 to 2016 were screened by multiplex PCR for RDRio identification, followed by 24-loci MIRU-VNTR and spoligotyping.

Results

A total number of 17 MTB RDRio strains were identified, representing an overall prevalence of 2.09% among MTB strains in Ecuador. While 10.9% of the MTB isolates included in the study were multidrug resistance (MDR), 29.4% (5/17) of the RDRio strains were MDR.

Discussion

This is the first report of the prevalence of MTB RDRio in Ecuador, where a strong association with MDR was found, but also a very low prevalence compared to other countries in Latin America. It is important to improve molecular epidemiology tools as a part of MTB surveillance programs in Latin America to track the transmission of potentially dangerous MTB stains associated to MDR TB like MTB RDRio.

Mathematical models of drug-resistant tuberculosis lack bacterial heterogeneity: A systematic review

Drug-resistant tuberculosis (DR-TB) threatens progress in the control of TB. Mathematical models are increasingly being used to guide public health decisions on managing both antimicrobial resistance (AMR) and TB. It is important to consider bacterial heterogeneity in models as it can have consequences for predictions of resistance prevalence, which may affect decision-making. We conducted a systematic review of published mathematical models to determine the modelling landscape and to explore methods for including bacterial heterogeneity. Our first objective was to identify and analyse the general characteristics of mathematical models of DR-mycobacteria, including M. tuberculosis. The second objective was to analyse methods of including bacterial heterogeneity in these models. We had different definitions of heterogeneity depending on the model level. For between-host models of mycobacterium, heterogeneity was defined as any model where bacteria of the same resistance level were further differentiated. For bacterial population models, heterogeneity was defined as having multiple distinct resistant populations. The search was conducted following PRISMA guidelines in five databases, with studies included if they were mechanistic or simulation models of DR-mycobacteria. We identified 195 studies modelling DR-mycobacteria, with most being dynamic transmission models of non-treatment intervention impact in M. tuberculosis (n = 58). Studies were set in a limited number of specific countries, and 44% of models (n = 85) included only a single level of "multidrug-resistance (MDR)". Only 23 models (8 between-host) included any bacterial heterogeneity. Most of these also captured multiple antibiotic-resistant classes (n = 17), but six models included heterogeneity in bacterial populations resistant to a single antibiotic. Heterogeneity was usually represented by different fitness values for bacteria resistant to the same antibiotic (61%, n = 14). A large and growing body of mathematical models of DR-mycobacterium is being used to explore intervention impact to support policy as well as theoretical explorations of resistance dynamics. However, the majority lack bacterial heterogeneity, suggesting that important evolutionary effects may be missed.

A protective role for type I interferon signaling following infection with Mycobacterium tuberculosis carrying the rifampicin drug resistance-conferring RpoB mutation H445Y

Interleukin-1 (IL-1) signaling is essential for controlling virulent Mycobacterium tuberculosis (Mtb) infection since antagonism of this pathway leads to exacerbated pathology and increased susceptibility. In contrast, the triggering of type I interferon (IFN) signaling is associated with the progression of tuberculosis (TB) disease and linked with negative regulation of IL-1 signaling. However, mice lacking IL-1 signaling can control Mtb infection if infected with an Mtb strain carrying the rifampin-resistance conferring mutation H445Y in its RNA polymerase β subunit (rpoB-H445Y Mtb). The mechanisms that govern protection in the absence of IL-1 signaling during rpoB-H445Y Mtb infection are unknown. In this study, we show that in the absence of IL-1 signaling, type I IFN signaling controls rpoB-H445Y Mtb replication, lung pathology, and excessive myeloid cell infiltration. Additionally, type I IFN is produced predominantly by monocytes and recruited macrophages and acts on LysM-expressing cells to drive protection through nitric oxide (NO) production to restrict intracellular rpoB-H445Y Mtb. These findings reveal an unexpected protective role for type I IFN signaling in compensating for deficiencies in IL-1 pathways during rpoB-H445Y Mtb infection.

Construction and validation of log odds of positive lymph nodes (LODDS)-based nomograms for predicting overall survival and cancer-specific survival in ovarian clear cell carcinoma patients

Background

Ovarian clear cell carcinoma (OCCC) is one of the special histologic subtypes of ovarian cancer. This study aimed to construct and validate log odds of positive lymph nodes (LODDS)-based nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with OCCC.

Methods

Patients who underwent surgical treatment between 2010 and 2016 were extracted from the Surveillance Epidemiology and End Results (SEER) database and the data of OCCC patients from the First Affiliated Hospital of Dalian Medical University were used as the external validation group to test the validity of the prognostic model. The best-fitting models were selected by stepwise Cox regression analysis. Survival probability was calculated by the Kaplan-Meier method, and the differences in survival time between subgroups were compared using the log-rank test. Each nomogram's performance was assessed by the calibration plots, decision curve analysis (DCA), and receiver operating characteristics (ROC) curves.

Results

T stage, distant metastasis, marital status, and LODDS were identified as significant risk factors for OS. A model with four risk factors (age, T stage, stage, and LODDS value) was obtained for CSS. Nomograms were constructed by incorporating the prognostic factors to predict 1-, 3- and 5-year OS and CSS for OCCC patients, respectively. The area under the curve (AUC) range of our nomogram model for OS and CSS prediction ranged from 0.738-0.771 and 0.769-0.794, respectively, in the training cohort. The performance of this model was verified in the internal and external validation cohorts. Calibration plots illustrated nomograms have good prognostic reliability.

Conclusion

Predictive nomograms were constructed and validated to evaluate the OS and CSS of OCCC patients. These nomograms may provide valuable prognostic information and guide postoperative personalized care in OCCC.

Compensatory mutations are associated with increased in vitro growth in resistant clinical samples of Mycobacterium tuberculosis

Mutations in Mycobacterium tuberculosis associated with resistance to antibiotics often come with a fitness cost for the bacteria. Resistance to the first-line drug rifampicin leads to lower competitive fitness of M. tuberculosis populations when compared to susceptible populations. This fitness cost, introduced by resistance mutations in the RNA polymerase, can be alleviated by compensatory mutations (CMs) in other regions of the affected protein. CMs are of particular interest clinically since they could lock in resistance mutations, encouraging the spread of resistant strains worldwide. Here, we report the statistical inference of a comprehensive set of CMs in the RNA polymerase of M. tuberculosis, using over 70 000 M. tuberculosis genomes that were collated as part of the CRyPTIC project. The unprecedented size of this data set gave the statistical tests more power to investigate the association of putative CMs with resistance-conferring mutations. Overall, we propose 51 high-confidence CMs by means of statistical association testing and suggest hypotheses for how they exert their compensatory mechanism by mapping them onto the protein structure. In addition, we were able to show an association of CMs with higher in vitro growth densities, and hence presumably with higher fitness, in resistant samples in the more virulent M. tuberculosis lineage 2. Our results suggest the association of CM presence with significantly higher in vitro growth than for wild-type samples, although this association is confounded with lineage and sub-lineage affiliation. Our findings emphasize the integral role of CMs and lineage affiliation in resistance spread and increases the urgency of antibiotic stewardship, which implies accurate, cheap and widely accessible diagnostics for M. tuberculosis infections to not only improve patient outcomes but also prevent the spread of resistant strains.

Micro-nanoemulsion and nanoparticle-assisted drug delivery against drug-resistant tuberculosis: recent developments

Tuberculosis (TB) is a major global health problem and the second most prevalent infectious killer after COVID-19. It is caused by Mycobacterium tuberculosis (Mtb) and has become increasingly challenging to treat due to drug resistance. The World Health Organization declared TB a global health emergency in 1993. Drug resistance in TB is driven by mutations in the bacterial genome that can be influenced by prolonged drug exposure and poor patient adherence. The development of drug-resistant forms of TB, such as multidrug resistant, extensively drug resistant, and totally drug resistant, poses significant therapeutic challenges. Researchers are exploring new drugs and novel drug delivery systems, such as nanotechnology-based therapies, to combat drug resistance. Nanodrug delivery offers targeted and precise drug delivery, improves treatment efficacy, and reduces adverse effects. Along with nanoscale drug delivery, a new generation of antibiotics with potent therapeutic efficacy, drug repurposing, and new treatment regimens (combinations) that can tackle the problem of drug resistance in a shorter duration could be promising therapies in clinical settings. However, the clinical translation of nanomedicines faces challenges such as safety, large-scale production, regulatory frameworks, and intellectual property issues. In this review, we present the current status, most recent findings, challenges, and limiting barriers to the use of emulsions and nanoparticles against drug-resistant TB.

Development of an Engineered Mycobacterium tuberculosis Strain for a Safe and Effective Tuberculosis Human Challenge Model

Human challenge experiments could greatly accelerate the development of a tuberculosis (TB) vaccine. Human challenge for tuberculosis requires a strain that can both replicate in the host and be reliably cleared. To accomplish this, we designed Mycobacterium tuberculosis (Mtb) strains featuring up to three orthogonal kill switches, tightly regulated by exogenous tetracyclines and trimethoprim. The resultant strains displayed immunogenicity and antibiotic susceptibility similar to wild-type Mtb under permissive conditions. In the absence of supplementary exogenous compounds, the strains were rapidly killed in axenic culture, mice and nonhuman primates. Notably, the strain that contained three kill switches had an escape rate of less than 10 -10 per genome per generation and displayed no relapse in a SCID mouse model. Collectively, these findings suggest that this engineered Mtb strain could be a safe and effective candidate for a human challenge model.

Prolonged survival of a patient with active MDR-TB HIV co-morbidity: insights from a Mycobacterium tuberculosis strain with a unique genomic deletion

Coinfection of HIV and multidrug-resistant tuberculosis (MDR-TB) presents significant challenges in terms of the treatment and prognosis of tuberculosis, leading to complexities in managing the disease and impacting the overall outcome for TB patients. This study presents a remarkable case of a patient with MDR-TB and HIV coinfection who survived for over 8 years, despite poor treatment adherence and comorbidities. Whole genome sequencing (WGS) of the infecting Mycobacterium tuberculosis (Mtb) strain revealed a unique genomic deletion, spanning 18 genes, including key genes involved in hypoxia response, intracellular survival, immunodominant antigens, and dormancy. This deletion, that we have called "Del-X," potentially exerts a profound influence on the bacterial physiology and its virulence. Only few similar deletions were detected in other non-related Mtb genomes worldwide. In vivo evolution analysis identified drug resistance and metabolic adaptation mutations and their temporal dynamics during the patient's treatment course.

Mycobacterium tuberculosis carrying the rifampicin drug-resistance-conferring rpoB mutation H445Y is associated with suppressed immunity through type I interferons

IMPORTANCE

This study highlights the impact of specific rifampicin-resistance-conferring mutations on the host immune response to Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB). Clinical reports have previously suggested that multi-drug-resistant) TB patients exhibit altered peripheral immune responses as compared with their drug-sensitive TB counterparts. The murine model of infection with Mtb strains carrying drug-resistance-conferring mutations recapitulated these findings and allowed us to mechanistically interrogate the pathways responsible for driving the divergent immune responses. Our findings underscore the need for greater investigation into bacterial heterogeneity to better appreciate the diversity in host-pathogen interactions during TB disease.

Mycobacterial DnaQ is an Alternative Proofreader Ensuring DNA Replication Fidelity

Remove of mis-incorporated nucleotides ensures replicative fidelity. Although the ε-exonuclease DnaQ is a well-established proofreader in the model organism Escherichia coli, proofreading in mycobacteria relies on the polymerase and histidinol phosphatase (PHP) domain of replicative polymerase despite the presence of an alternative DnaQ homolog. Here, we show that depletion of DnaQ in Mycolicibacterium smegmatis results in increased mutation rate, leading to AT-biased mutagenesis and elevated insertions/deletions in homopolymer tract. We demonstrated that mycobacterial DnaQ binds to the b-clamp and functions synergistically with the PHP domain to correct replication errors. Further, we found that the mycobacterial DnaQ sustains replicative fidelity upon chromosome topological stress. Intriguingly, we showed that a naturally evolved DnaQ variant prevalent in clinical Mycobacterium tuberculosis isolates enables hypermutability and is associated with extensive drug resistance. These results collectively establish that the alternative DnaQ functions in proofreading, and thus reveal that mycobacteria deploy two proofreaders to maintain replicative fidelity.

Mycobacterium tuberculosis infection drives differential responses in the bone marrow hematopoietic stem and progenitor cells

Hematopoietic stem and progenitor cells (HSPCs) play a vital role in the host response to infection through the rapid and robust production of mature immune cells. These HSPC responses can be influenced, directly and indirectly, by pathogens as well. Infection with Mycobacterium tuberculosis (Mtb) can drive lymphopoiesis through modulation of type I interferon (IFN) signaling. We have previously found that the presence of a drug resistance (DR)-conferring mutation in Mtb drives altered host-pathogen interactions and heightened type I IFN production in vitro. But the impacts of this DR mutation on in vivo host responses to Mtb infection, particularly the hematopoietic compartment, remain unexplored. Using a mouse model, we show that, while drug-sensitive Mtb infection induces expansion of HSPC subsets and a skew toward lymphopoiesis, DR Mtb infection fails to induce an expansion of these subsets and an accumulation of mature granulocytes in the bone marrow. Using single-cell RNA sequencing, we show that the HSCs from DR Mtb-infected mice fail to upregulate pathways related to cytokine signaling across all profiled HSC subsets. Collectively, our studies report a novel finding of a chronic infection that fails to induce a potent hematopoietic response that can be further investigated to understand pathogen-host interaction at the level of hematopoiesis.

Mixed infections in genotypic drug-resistant Mycobacterium tuberculosis

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis, is a major global public health problem, resulting in more than 1 million deaths each year. Drug resistance (DR), including multi-drug (MDR-TB), is making TB control difficult and accounts for 16% of new and 48% of previously treated cases. To further complicate treatment decision-making, many clinical studies have reported patients harbouring multiple distinct strains of M. tuberculosis across the main lineages (L1 to L4). The extent to which drug-resistant strains can be deconvoluted within mixed strain infection samples is understudied. Here, we analysed M. tuberculosis isolates with whole genome sequencing data (n = 50,723), which covered the main lineages (L1 9.1%, L2 27.6%, L3 11.8%, L4 48.3%), with genotypic resistance to isoniazid (HR-TB; n = 9546 (29.2%)), rifampicin (RR-TB; n = 7974 (24.4%)), and at least MDR-TB (n = 5385 (16.5%)). TB-Profiler software revealed 531 (1.0%) isolates with potential mixed sub-lineage infections, including some with DR mutations (RR-TB 21/531; HR-TB 59/531; at least MDR-TB 173/531). To assist with the deconvolution of such mixtures, we adopted and evaluated a statistical Gaussian Mixture model (GMM) approach. By simulating 240 artificial mixtures of different ratios from empirical data across L1 to L4, a GMM approach was able to accurately estimate the DR profile of each lineage, with a low error rate for the estimated mixing proportions (mean squared error 0.012) and high accuracy for the DR predictions (93.5%). Application of the GMM model to the clinical mixtures (n = 531), found that 33.3% (188/531) of samples consisted of DR and sensitive lineages, 20.2% (114/531) consisted of lineages with only DR mutations, and 40.6% (229/531) consisted of lineages with genotypic pan-susceptibility. Overall, our work demonstrates the utility of combined whole genome sequencing data and GMM statistical analysis approaches for providing insights into mono and mixed M. tuberculosis infections, thereby potentially assisting diagnosis, treatment decision-making, drug resistance and transmission mapping for infection control.

The Mycobacterium tuberculosis genome at 25 years: lessons and lingering questions

First achieved in 1998 by Cole et al., the complete genome sequence of Mycobacterium tuberculosis continues to provide an invaluable resource to understand tuberculosis (TB), the leading cause of global infectious disease mortality. At the 25-year anniversary of this accomplishment, we describe how insights gleaned from the M. tuberculosis genome have led to vital tools for TB research, epidemiology, and clinical practice. The increasing accessibility of whole-genome sequencing across research and clinical settings has improved our ability to predict antibacterial susceptibility, to track epidemics at the level of individual outbreaks and wider historical trends, to query the efficacy of the bacille Calmette-Guérin (BCG) vaccine, and to uncover targets for novel antitubercular therapeutics. Likewise, we discuss several recent efforts to extract further discoveries from this powerful resource.

Insight into the drug-resistant characteristics and genetic diversity of multidrug-resistant Mycobacterium tuberculosis in China

Multidrug-resistant tuberculosis (MDR-TB) has a severe impact on public health. To investigate the drug-resistant profile, compensatory mutations and genetic variations among MDR-TB isolates, a total of 546 MDR-TB isolates from China underwent drug-susceptibility testing and whole genome sequencing for further analysis. The results showed that our isolates have a high rate of fluoroquinolone resistance (45.60%, 249/546) and a low proportion of conferring resistance to bedaquiline, clofazimine, linezolid, and delamanid. The majority of MDR-TB isolates (77.66%, 424/546) belong to Lineage 2.2.1, followed by Lineage 4.5 (6.41%, 35/546), and the Lineage 2 isolates have a strong association with pre-XDR/XDR-TB (P < 0.05) in our study. Epidemic success analysis using time-scaled haplotypic density (THD) showed that clustered isolates outperformed non-clustered isolates. Compensatory mutations happened in rpoA, rpoC, and non-RRDR of rpoB genes, which were found more frequently in clusters and were associated with the increase of THD index, suggesting that increased bacterial fitness was associated with MDR-TB transmission. In addition, the variants in resistance associated genes in MDR isolates are mainly focused on single nucleotide polymorphism mutations, and only a few genes have indel variants, such as katG, ethA. We also found some genes underwent indel variation correlated with the lineage and sub-lineage of isolates, suggesting the selective evolution of different lineage isolates. Thus, this analysis of the characterization and genetic diversity of MDR isolates would be helpful in developing effective strategies for treatment regimens and tailoring public interventions. IMPORTANCE Multidrug-resistant tuberculosis (MDR-TB) is a serious obstacle to tuberculosis prevention and control in China. This study provides insight into the drug-resistant characteristics of MDR combined with phenotypic drug-susceptibility testing and whole genome sequencing. The compensatory mutations and epidemic success analysis were analyzed by time-scaled haplotypic density (THD) method, suggesting clustered isolates and compensatory mutations are associated with MDR-TB transmission. In addition, the insertion and deletion variants happened in some genes, which are associated with the lineage and sub-lineage of isolates, such as the mpt64 gene. This study offered a valuable reference and increased understanding of MDR-TB in China, which could be crucial for achieving the objective of precision medicine in the prevention and treatment of MDR-TB.

Comparative Study on Tuberculosis Drug Resistance and Molecular Detection Methods Among Different Mycobacterium Tuberculosis Lineages

Purpose

This study aims to compare drug resistance and detection efficacy across different Mycobacterium tuberculosis lineages, offering insights for precise treatment and molecular diagnosis.

Methods

161 strains of Mycobacterium tuberculosis (M.tb) were tested for drug resistance using Phenotypic Drug Susceptibility Testing (pDST), High-Resolution Melting analysis (HRM), and Whole Genome Sequencing (WGS) methods. The main focus was on evaluating the accuracy of different methods for detecting resistance to rifampicin (RIF), isoniazid (INH), and streptomycin (SM).

Results

Among the 161 strains of M.tb, 83.85% (135/161) were fully sensitive to RIF, INH, and SM according to pDST, and the rate of multidrug resistance was 4.35% (7/161). The drug resistance rates of lineage 2 M.tb to the three drugs (26/219, 11.87%) were significantly higher than those of non-lineage 2 M.tb (12/264, 4.45%) (P<0.05). Compared with pDST, WGS had a sensitivity of 100%, 94.12%, and 92.31% and a specificity of 100%, 99.31%, and 98.65% for RIF, INH, and SM, respectively, with no significant difference. The sensitivity of HRM for RIF, INH, and SM was 87.50%, 52.94%, and 76.92%, respectively, while the specificity was 96.08%, 99.31%, and 99.32%, respectively. The sensitivity of HRM for detecting INH resistance was significantly lower than that of pDST (P=0.039). Compared with HRM, WGS increased the sensitivity of RIF, INH, and SM by 12.50%, 41.18%, and 15.38%, respectively.

Conclusion

There are significant differences in drug resistance rates among different lineages of M.tb, with lineage 2 having higher rates of RIF, INH, and SM resistance than lineages 3 and 4. The sensitivity of HRM is far lower than that of pDST, and currently, the accuracy of HRM is not sufficient to replace pDST. WGS has no significant difference in detecting drug resistance compared with pDST but can identify new anti-tuberculosis drug-resistant mutations, providing effective guidance for clinical decision-making.

Borderline rpoB mutations transmit at the same rate as common rpoB mutations in a tuberculosis cohort in Bangladesh

The spread of multidrug-resistant tuberculosis (MDR-TB) is a growing problem in many countries worldwide. Resistance to one of the primary first-line drugs, rifampicin, is caused by mutations in the Mycobacterium tuberculosis rpoB gene. So-called borderline rpoB mutations confer low-level resistance, in contrast to more common rpoB mutations which confer high-level resistance. While some borderline mutations show lower fitness in vitro than common mutations, their in vivo fitness is currently unknown. We used a dataset of 394 whole genome sequenced MDR-TB isolates from Bangladesh, representing around 44 % of notified MDR-TB cases over 6 years, to look at differences in transmission clustering between isolates with borderline rpoB mutations and those with common rpoB mutations. We found a relatively low percentage of transmission clustering in the dataset (34.8 %) but no difference in clustering between different types of rpoB mutations. Compensatory mutations in rpoA, rpoB, and rpoC were associated with higher levels of transmission clustering as were lineages two, three, and four relative to lineage one. Young people as well as patients with high sputum smear positive TB were more likely to be in a transmission cluster. Our findings show that although borderline rpoB mutations have lower in vitro growth potential this does not translate into lower transmission potential or in vivo fitness. Proper detection of these mutations is crucial to ensure they do not go unnoticed and spread MDR-TB within communities.

The utility of SARS-CoV-2 genomic data for informative clustering under different epidemiological scenarios and sampling

OBJECTIVES

Clustering pathogen sequence data is a common practice in epidemiology to gain insights into the genetic diversity and evolutionary relationships among pathogens. We can find groups of cases with a shared transmission history and common origin, as well as identifying transmission hotspots. Motivated by the experience of clustering SARS-CoV-2 cases using whole genome sequence data during the COVID-19 pandemic to aid with public health investigation, we investigated how differences in epidemiology and sampling can influence the composition of clusters that are identified.

METHODS

We performed genomic clustering on simulated SARS-CoV-2 outbreaks produced with different transmission rates and levels of genomic diversity, along with varying the proportion of cases sampled.

RESULTS

In single outbreaks with a low transmission rate, decreasing the sampling fraction resulted in multiple, separate clusters being identified where intermediate cases in transmission chains are missed. Outbreaks simulated with a high transmission rate were more robust to changes in the sampling fraction and largely resulted in a single cluster that included all sampled outbreak cases. When considering multiple outbreaks in a sampled jurisdiction seeded by different introductions, low genomic diversity between introduced cases caused outbreaks to be merged into large clusters. If the transmission and sampling fraction, and diversity between introductions was low, a combination of the spurious break-up of outbreaks and the linking of closely related cases in different outbreaks resulted in clusters that may appear informative, but these did not reflect the true underlying population structure. Conversely, genomic clusters matched the true population structure when there was relatively high diversity between introductions and a high transmission rate.

CONCLUSION

Differences in epidemiology and sampling can impact our ability to identify genomic clusters that describe the underlying population structure. These findings can help to guide recommendations for the use of pathogen clustering in public health investigations.

Disruption of Aldehyde Dehydrogenase 2 protects against bacterial infection

The ALDH2*2 (rs671) allele is one of the most common genetic mutations in humans, yet the positive evolutionary selective pressure to maintain this mutation is unknown, despite its association with adverse health outcomes. ALDH2 is responsible for the detoxification of metabolically produced aldehydes, including lipid-peroxidation end products derived from inflammation. Here, we demonstrate that host-derived aldehydes 4-hydroxynonenal (4HNE), malondialdehyde (MDA), and formaldehyde (FA), all of which are metabolized by ALDH2, are directly toxic to the bacterial pathogens Mycobacterium tuberculosis and Francisella tularensis at physiological levels. We find that Aldh2 expression in macrophages is decreased upon immune stimulation, and that bone marrow-derived macrophages from Aldh2 -/- mice contain elevated aldehydes relative to wild-type mice. Macrophages deficient for Aldh2 exhibited enhanced control of Francisella infection. Finally , mice lacking Aldh2 demonstrated increased resistance to pulmonary infection by M. tuberculosis , including in a hypersusceptible model of tuberculosis, and were also resistant to Francisella infection. We hypothesize that the absence of ALDH2 contributes to the host's ability to control infection by pathogens such as M. tuberculosis and F. tularensis , and that host-derived aldehydes act as antimicrobial factors during intracellular bacterial infections.

One sentence summary

Aldehydes produced by host cells contribute to the control of bacterial infections.

Molecular epidemiology and transmission dynamics of multi-drug resistant tuberculosis strains using whole genome sequencing in the Amhara region, Ethiopia

BACKGROUND

Drug resistant Mycobacterium tuberculosis prevention and care is a major challenge in Ethiopia. The World health organization has designated Ethiopia as one of the 30 high burden multi-drug resistant tuberculosis (MDR-TB) countries. There is limited information regarding genetic diversity and transmission dynamics of MDR-TB in Ethiopia.

OBJECTIVE

To investigate the molecular epidemiology and transmission dynamics of MDR-TB strains using whole genome sequence (WGS) in the Amhara region.

METHODS

Forty-five MDR-TB clinical isolates from Amhara region were collected between 2016 and 2018, and characterized using WGS and 24-loci Mycobacterium Interspersed Repetitive Units Variable Number of Tandem Repeats (MIRU-VNTR) typing. Clusters were defined based on the maximum distance of 12 single nucleotide polymorphisms (SNPs) or alleles as the upper threshold of genomic relatedness. Five or less SNPs or alleles distance or identical 24-loci VNTR typing is denoted as surrogate marker for recent transmission.

RESULTS

Forty-one of the 45 isolates were analyzed by WGS and 44% (18/41) of the isolates were distributed into 4 clusters. Of the 41 MDR-TB isolates, 58.5% were classified as lineage 4, 36.5% lineage 3 and 5% lineage 1. Overall, TUR genotype (54%) was the predominant in MDR-TB strains. 41% (17/41) of the isolates were clustered into four WGS groups and the remaining isolates were unique strains. The predominant cluster (Cluster 1) was composed of nine isolates belonging to lineage 4 and of these, four isolates were in the recent transmission links.

CONCLUSIONS

Majority of MDR-TB strain cluster and predominance of TUR lineage in the Amhara region give rise to concerns for possible ongoing transmission. Efforts to strengthen TB laboratory to advance diagnosis, intensified active case finding, and expanded contact tracing activities are needed in order to improve rapid diagnosis and initiate early treatment. This would lead to the interruption of the transmission chain and stop the spread of MDR-TB in the Amhara region.

Frequency of rifampicin-resistant mycobacterium tuberculosis by GeneXpert MTB/RIF assay and its correlates among 2605 probable tuberculosis patients in upper Egypt

RATIONALE

GeneXpert MTB/RIF (Mycobacterium tuberculosis/rifampicin) assay is a method for detecting rifampicin resistance (RR-MTB) in suspected samples in less than 2 hours with high sensitivity and specificity yield. This study aimed to use the GeneXpert MTB/RIF assay to determine the frequency of RR-MTB and to study the possible influencing correlates associated with positive results.

SUBJECTS AND METHODS

This is a retrospective cross-sectional study of patients who visited TB clinic in 5 years (2016-2021). According to the data sheet of the patients, all the collected specimens were divided into 2 parts one for diagnosis by Ziehl-Neelsen stain and the other part for GeneXpert analysis. GeneXpert was also used to look for evidence of RR.

RESULTS

Out of the 2605 total samples screened, 718 (27.6%) tested positive for MTB on GeneXpert assay; of them 633 (88.4%) were sensitive to Rifampicin, 83 (11.6%) were resistant to Rifampicin and 2 cases were undetermined. Factors contributing to RR-MTB were: smoker/ex-smoker, with 2.5 times more risk (p = 0.013.0, p = 0.001); recurrence cases had a 4-fold increased risk (p < 0.001); patients with very low M. tuberculosis detected on the GeneXpert MTB/RIF test were 8 times more likely to have RR-TB (P = 0.004).

CONCLUSION

This study disclosed a high-rate MTB in Egyptian probable TB cases. Smoking, recurrence and cases with a very low M. tuberculosis burden noticed on the GeneXpert MTB/RIF test had augmented risk of RR-TB.

Sequential mutations in exponentially growing populations

Stochastic models of sequential mutation acquisition are widely used to quantify cancer and bacterial evolution. Across manifold scenarios, recurrent research questions are: how many cells are there with n alterations, and how long will it take for these cells to appear. For exponentially growing populations, these questions have been tackled only in special cases so far. Here, within a multitype branching process framework, we consider a general mutational path where mutations may be advantageous, neutral or deleterious. In the biologically relevant limiting regimes of large times and small mutation rates, we derive probability distributions for the number, and arrival time, of cells with n mutations. Surprisingly, the two quantities respectively follow Mittag-Leffler and logistic distributions regardless of n or the mutations' selective effects. Our results provide a rapid method to assess how altering the fundamental division, death, and mutation rates impacts the arrival time, and number, of mutant cells. We highlight consequences for mutation rate inference in fluctuation assays.

The relative transmission fitness of multidrug-resistant Mycobacterium tuberculosis in a drug resistance hotspot

Multidrug-resistant tuberculosis (MDR-TB) is among the most frequent causes of death due to antimicrobial resistance. Although only 3% of global TB cases are MDR, geographical hotspots with up to 40% of MDR-TB have been observed in countries of the former Soviet Union. While the quality of TB control and patient-related factors are known contributors to such hotspots, the role of the pathogen remains unclear. Here we show that in the country of Georgia, a known hotspot of MDR-TB, MDR Mycobacterium tuberculosis strains of lineage 4 (L4) transmit less than their drug-susceptible counterparts, whereas most MDR strains of L2 suffer no such defect. Our findings further indicate that the high transmission fitness of these L2 strains results from epistatic interactions between the rifampicin resistance-conferring mutation RpoB S450L, compensatory mutations in the RNA polymerase, and other pre-existing genetic features of L2/Beijing clones that circulate in Georgia. We conclude that the transmission fitness of MDR M. tuberculosis strains is heterogeneous, but can be as high as drug-susceptible forms, and that such highly drug-resistant and transmissible strains contribute to the emergence and maintenance of hotspots of MDR-TB. As these strains successfully overcome the metabolic burden of drug resistance, and given the ongoing rollout of new treatment regimens against MDR-TB, proper surveillance should be implemented to prevent these strains from acquiring resistance to the additional drugs.

Clinical implications of molecular drug resistance testing for Mycobacterium tuberculosis: a 2023 TBnet/RESIST-TB consensus statement

Drug-resistant tuberculosis is a substantial health-care concern worldwide. Despite culture-based methods being considered the gold standard for drug susceptibility testing, molecular methods provide rapid information about the Mycobacterium tuberculosis mutations associated with resistance to anti-tuberculosis drugs. This consensus document was developed on the basis of a comprehensive literature search, by the TBnet and RESIST-TB networks, about reporting standards for the clinical use of molecular drug susceptibility testing. Review and the search for evidence included hand-searching journals and searching electronic databases. The panel identified studies that linked mutations in genomic regions of M tuberculosis with treatment outcome data. Implementation of molecular testing for the prediction of drug resistance in M tuberculosis is key. Detection of mutations in clinical isolates has implications for the clinical management of patients with multidrug-resistant or rifampicin-resistant tuberculosis, especially in situations when phenotypic drug susceptibility testing is not available. A multidisciplinary team including clinicians, microbiologists, and laboratory scientists reached a consensus on key questions relevant to molecular prediction of drug susceptibility or resistance to M tuberculosis, and their implications for clinical practice. This consensus document should help clinicians in the management of patients with tuberculosis, providing guidance for the design of treatment regimens and optimising outcomes.

The evolution of antibiotic resistance is associated with collateral drug phenotypes in Mycobacterium tuberculosis

The increasing incidence of drug resistance in Mycobacterium tuberculosis has diminished the efficacy of almost all available antibiotics, complicating efforts to combat the spread of this global health burden. Alongside the development of new drugs, optimised drug combinations are needed to improve treatment success and prevent the further spread of antibiotic resistance. Typically, antibiotic resistance leads to reduced sensitivity, yet in some cases the evolution of drug resistance can lead to enhanced sensitivity to unrelated drugs. This phenomenon of collateral sensitivity is largely unexplored in M. tuberculosis but has the potential to identify alternative therapeutic strategies to combat drug-resistant strains that are unresponsive to current treatments. Here, by using drug susceptibility profiling, genomics and evolutionary studies we provide evidence for the existence of collateral drug sensitivities in an isogenic collection M. tuberculosis drug-resistant strains. Furthermore, in proof-of-concept studies, we demonstrate how collateral drug phenotypes can be exploited to select against and prevent the emergence of drug-resistant strains. This study highlights that the evolution of drug resistance in M. tuberculosis leads to collateral drug responses that can be exploited to design improved drug regimens.

The Evolution and Transmission Dynamics of Multidrug-Resistant Tuberculosis in an Isolated High-Plateau Population of Tibet, China

On the Tibetan Plateau, most tuberculosis is caused by indigenous Mycobacterium tuberculosis strains with a monophyletic structure and high-level drug resistance. This study investigated the emergence, evolution, and transmission dynamics of multidrug-resistant tuberculosis (MDR-TB) in Tibet. The whole-genome sequences of 576 clinical strains from Tibet were analyzed with the TB-profiler tool to identify drug-resistance mutations. The evolution of the drug resistance was then inferred based on maximum-likelihood phylogeny and dated trees that traced the serial acquisition of mutations conferring resistance to different drugs. Among the 576 clinical M. tuberculosis strains, 346 (60.1%) carried at least 1 resistance-conferring mutation and 231 (40.1%) were MDR-TB. Using a pairwise distance of 50 single nucleotide polymorphisms (SNPs), most strains (89.9%, 518/576) were phylogenetically separated into 50 long-term transmission clusters. Eleven large drug-resistant clusters contained 76.1% (176/231) of the local multidrug-resistant strains. A total of 85.2% of the isoniazid-resistant strains were highly transmitted with an average of 6.6 cases per cluster, of which most shared the mutation KatG Ser315Thr. A lower proportion (71.6%) of multidrug-resistant strains were transmitted, with an average cluster size of 2.9 cases. The isoniazid-resistant clusters appear to have undergone substantial bacterial population growth in the 1970s to 1990s and then subsequently accumulated multiple rifampicin-resistance mutations and caused the current local MDR-TB burden. These findings highlight the importance of detecting and curing isoniazid-resistant strains to prevent the emergence of endemic MDR-TB. IMPORTANCE Emerging isoniazid resistance in the 1970s allowed M. tuberculosis strains to spread and form into large multidrug-resistant tuberculosis clusters in the isolated plateau of Tibet, China. The epidemic was driven by the high risk of transmission as well as the potential of acquiring further drug resistance from isoniazid-resistant strains. Eleven large drug-resistant clusters consisted of the majority of local multidrug-resistant cases. Among the clusters, isoniazid resistance overwhelmingly evolved before all the other resistance types. A large bacterial population growth of isoniazid-resistant clusters occurred between 1970s and 1990s, which subsequently accumulated rifampicin-resistance-conferring mutations in parallel and accounted for the local multidrug-resistant tuberculosis burden. The results of our study indicate that it may be possible to restrict MDR-TB evolution and dissemination by prioritizing screening for isoniazid (INH)-resistant TB strains before they become MDR-TB and by adopting measures that can limit their transmission.

Strain diversity and gene mutations associated with presumptive multidrug-resistant Mycobacterium tuberculosis complex isolates in Northwest Ethiopia

OBJECTIVES

In this study, we assessed the genetic diversity and gene mutations that confer resistance to rifampicin (RIF), isoniazid (INH), fluoroquinolone (FQ), and second-line injectable (SLI) drugs in RIF-resistant (RR)/multidrug-resistant tuberculosis (MDR-TB) isolates in Northwest Ethiopia.

METHODS

Spoligotyping was used to assign isolates to TB lineages (Ls), and Hain line probe assays were used to detect resistance to RIF, INH, and FQs, and SLIs.

RESULTS

Among 130 analyzed strains, 68.5% were RR, and four major Mycobacterium tuberculosis complex lineages (L1, L3, L4, and L7) were identified with a predominance of the Euro-American L4 (72, 54.7%), while L7 genotypes were less common (3, 2.3%). Overall, the L4-T3-ETH (41, 32.0%), L3-CAS1-Delhi (29, 22.7%), and L3-CAS1-Killi (19, 14.8%) families were most common. Line probe analysis showed that among rpoB mutants, 65.2% were S450L, while 87.8% of katG mutants were S315T. Only three isolates showed mutation (c-15t) at the inhA gene, and no double mutation with katG and inhA genes was found. Six strains, two each of L1, L3, and L4, were resistant to FQs, having gyrA mutations (D94G, S91P), of which three isolates had additional resistance to SLI (rrs A1401G or C1402T mutations) including one isolate with low-level kanamycin (KAN) resistance.

CONCLUSIONS

This study showed a predominance of L4-T3-ETH, L3-CAS1-Delhi, and L3-CAS1-Killi families, with a high rate of rpoB_S450L and katG_S315T mutations and a low proportion of gyrA and rrs mutations. L7 was less frequently observed in this study. Further investigations are, therefore, needed to understand L7 and other lineages with undefined mutations.

GWAS and functional studies suggest a role for altered DNA repair in the evolution of drug resistance in Mycobacterium tuberculosis

The emergence of drug resistance in Mycobacterium tuberculosis (Mtb) is alarming and demands in-depth knowledge for timely diagnosis. We performed genome-wide association analysis using 2237 clinical strains of Mtb to identify novel genetic factors that evoke drug resistance. In addition to the known direct targets, we identified for the first time, a strong association between mutations in DNA repair genes and the multidrug-resistant phenotype. To evaluate the impact of variants identified in the clinical samples in the evolution of drug resistance, we utilized knockouts and complemented strains in Mycobacterium smegmatis and Mtb. Results show that variant mutations compromised the functions of MutY and UvrB. MutY variant showed enhanced survival compared with wild-type (Rv) when the Mtb strains were subjected to multiple rounds of ex vivo antibiotic stress. In an in vivo guinea pig infection model, the MutY variant outcompeted the wild-type strain. We show that novel variant mutations in the DNA repair genes collectively compromise their functions and contribute to better survival under antibiotic/host stress conditions.

Genetic Diversity and Primary Drug Resistance of Mycobacterium tuberculosis Beijing Genotype Strains in Northwestern Russia

The Beijing genotype is the main family of Mycobacterium tuberculosis in Russia. We analyzed its diversity and drug resistance in provinces across Northwestern Russia to identify the epidemiologically relevant Beijing strains. The study collection included 497 isolates from newly-diagnosed tuberculosis (TB) patients. Bacterial isolates were subjected to drug-susceptibility testing and genotyping. The Beijing genotype was detected in 57.5% (286/497); 50% of the Beijing strains were multidrug-resistant (MDR). Central Asian/Russian and B0/W148 groups included 176 and 77 isolates, respectively. MDR was more frequent among B0/W148 strains compared to Central Asian/Russian strains (85.7% vs. 40.3%, p < 0.0001). Typing of 24 minisatellite loci of Beijing strains revealed 82 profiles; 230 isolates were in 23 clusters. The largest Central Asian/Russian types were 94-32 (n = 75), 1065-32 (n = 17), and 95-32 (n = 12). B0/W148 types were 100-32 (n = 59) and 4737-32 (n = 5). MDR was more frequent in types 1065-32 (88.2%), 100-32 (83.1%), and 4737-32 (100%). In contrast, type 9391-32 (n = 9) included only drug-susceptible strains. To conclude, M. tuberculosis Beijing genotype is dominant in Northwestern Russia, and an active transmission of overwhelmingly MDR B0/W148 types explains the reported increase of MDR-TB. The presence of MDR-associated minor variants (type 1071-32/ancient Beijing and Central Asia Outbreak strain) in some of the studied provinces also requires attention.

Advances in the design of combination therapies for the treatment of tuberculosis

INTRODUCTION

Tuberculosis requires lengthy multi-drug therapy. Mycobacterium tuberculosis occupies different tissue compartments during infection, making drug access and susceptibility patterns variable. Antibiotic combinations are needed to ensure each compartment of infection is reached with effective drug treatment. Despite drug combinations' role in treating tuberculosis, the design of such combinations has been tackled relatively late in the drug development process, limiting the number of drug combinations tested. In recent years, there has been significant progress using in vitro, in vivo, and computational methodologies to interrogate combination drug effects.

AREAS COVERED

This review discusses the advances in these methodologies and how they may be used in conjunction with new successful clinical trials of novel drug combinations to design optimized combination therapies for tuberculosis. Literature searches for approaches and experimental models used to evaluate drug combination effects were undertaken.

EXPERT OPINION

We are entering an era richer in combination drug effect and pharmacokinetic/pharmacodynamic data, genetic tools, and outcome measurement types. Application of computational modeling approaches that integrate these data and produce predictive models of clinical outcomes may enable the field to generate novel, effective multidrug therapies using existing and new drug combination backbones.

Connecting the dots: understanding how human mobility shapes TB epidemics

Tuberculosis (TB) remains a leading infectious cause of death worldwide. Reducing TB infections and TB-related deaths rests ultimately on stopping forward transmission from infectious to susceptible individuals. Critical to this effort is understanding how human host mobility shapes the transmission and dispersal of new or existing strains of Mycobacterium tuberculosis (Mtb). Important questions remain unanswered. What kinds of mobility, over what temporal and spatial scales, facilitate TB transmission? How do human mobility patterns influence the dispersal of novel Mtb strains, including emergent drug-resistant strains? This review summarizes the current state of knowledge on mobility and TB epidemic dynamics, using examples from three topic areas, including inference of genetic and spatial clustering of infections, delineating source-sink dynamics, and mapping the dispersal of novel TB strains, to examine scientific questions and methodological issues within this topic. We also review new data sources for measuring human mobility, including mobile phone-associated movement data, and discuss important limitations on their use in TB epidemiology.

Low-Level Cefepime Exposure Induces High-Level Resistance in Environmental Bacteria: Molecular Mechanism and Evolutionary Dynamics

Antibiotics exert selective pressures on clinically relevant antibiotic resistance. It is critical to understand how antibiotic resistance evolves in environmental microbes exposed to subinhibitory concentrations of antibiotics and whether evolutionary dynamics and emergence of resistance are predictable. In this study, Comamonas testosteroni isolated from wastewater activated sludge were subcultured in a medium containing 10 ng/mL cefepime for 40 days (∼300 generations). Stepwise mutations were accumulated, leading to an ultimate 200-fold increase in the minimum inhibitory concentration (MIC) of cefepime. Early stage mutation in DNA polymerase-encoding gene dnaE2 played an important role in antibiotic resistance evolution. Diverse resistance mechanisms were employed and validated experimentally, including increased efflux, biofilm formation, reduced antibiotic uptake, and drug inactivation. The cefepime minimal selective concentrations (MSCs) and relative fitness of susceptible, intermediate, and resistant mutants were determined. Agent-based modeling of the modified Moran process enabled simulations of resistance evolution and predictions of the emergence time and frequency of resistant mutants. The unraveled cefepime resistance mechanisms could be employed by broader bacteria, and the newly developed model is applicable to the predictions of general resistance evolution. The improved knowledge facilitates the assessment, prediction, and mitigation of antibiotic resistance progression in antibiotic-polluted environments.

Rapid Identification of Drug Resistance and Phylogeny in M. tuberculosis, Directly from Sputum Samples

Tuberculosis (TB) remains one of the most important infectious diseases globally. Establishing a resistance profile from the initial TB diagnosis is a priority. Rapid molecular tests evaluate only the most common genetic variants responsible for resistance to certain drugs, and Whole Genome Sequencing (WGS) needs culture prior to next-generation sequencing (NGS), limiting their clinical value. Targeted sequencing (TS) from clinical samples avoids these drawbacks, providing a signature of genetic markers that can be associated with drug resistance and phylogeny. In this study, a proof-of-concept protocol was developed for detecting genomic variants associated with drug resistance and for the phylogenetic classification of Mycobacterium Tuberculosis (Mtb) in sputum samples. Initially, a set of Mtb reference strains from the WHO were sequenced (WGS and TS). The results from the protocol agreed >95% with WHO reported data and phenotypic drug susceptibility testing (pDST). Lineage genetics results were 100% concordant with those derived from WGS. After that, the TS protocol was applied to sputum samples from TB patients to detect resistance to first- and second-line drugs and derive phylogeny. The accuracy was >90% for all evaluated drugs, except Eto/Pto (77.8%), and 100% were phylogenetically classified. The results indicate that the described protocol, which affords the complete drug resistance profile and phylogeny of Mtb from sputum, could be useful in the clinical area, advancing toward more personalized and more effective treatments in the near future. IMPORTANCE The COVID-19 pandemic negatively affected the progress in accessing essential Tuberculosis (TB) services and reducing the burden of TB disease, resulting in a decreased detection of new cases and increased deaths. Generating molecular diagnostic tests with faster results without losing reliability is considered a priority. Specifically, developing an antimicrobial resistance profile from the initial stages of TB diagnosis is essential to ensure appropriate treatment. Currently available rapid molecular tests evaluate only the most common genetic variants responsible for resistance to certain drugs, limiting their clinical value. In this work, targeted sequencing on sputum samples from TB patients was used to identify Mycobacterium tuberculosis mutations in genes associated with drug resistance and to derive a phylogeny of the infecting strain. This protocol constitutes a proof-of-concept toward the goal of helping clinicians select a timely and appropriate treatment by providing them with actionable information beyond current molecular approaches.

Evolution of Mycobacterium tuberculosis drug resistance in the genomic era

Mycobacterium tuberculosis has acquired drug resistance to all drugs that have been used against it, including those only recently introduced into clinical practice. Compared to other bacteria, it has a well conserved genome due to its role as an obligate human pathogen that has adapted to a niche over five to ten thousand years. These features facilitate reconstruction and dating of M. tuberculosis phylogenies, giving key insights into how resistance has been acquired and spread globally. Resistance to each new drug has occurred within five to ten years of clinical use and has occurred even more rapidly with recently introduced drugs. In most cases, resistance-conferring mutations come with a fitness cost, but this can be overcome by compensatory mutations which restore fitness to that of wild-type bacteria. It is likely that M. tuberculosis acquires drug resistance while maintaining limited genomic variability due the generation of low frequency within-host variation, combined with ongoing purifying selection causing loss of variants without a clear fitness advantage. However, variants that do confer an advantage, such as drug resistance, can increase in prevalence amongst all bacteria within a host and become the dominant clone. These resistant strains can then be transmitted leading to primary drug resistant infection in a new host. As many countries move towards genomic methods for diagnosis of M. tuberculosis infection and drug resistance, it is important to be aware of the implications for the evolution of resistance. Currently, understanding of resistance-conferring mutations is incomplete, and some targeted genetic diagnostics create their own selective pressures. We discuss an example where a rifampicin resistance-conferring mutation which was not routinely covered by standard testing became dominant. Finally, resistance to new drugs such as bedaquiline and delamanid is caused by individually rare mutations occurring across a large mutational genomic target that have been detected over a short time, and do not provide statistical power for genotype-phenotype correlation – in contrast to longer-established drugs that form the backbone of drug-sensitive antituberculosis therapy. Therefore, we need a different approach to identify resistance-conferring mutations of new drugs before their resistance becomes widespread, abrogating their usefulness.

Mycobacterium tuberculosis functional genetic diversity, altered drug sensitivity, and precision medicine

In the face of the unrelenting global burden of tuberculosis (TB), antibiotics remain our most effective tools to save lives and control the spread of Mycobacterium tuberculosis (Mtb). However, we confront a dual challenge in our use of antibiotics: simplifying and shortening the TB drug regimen while also limiting the emergence and propagation of antibiotic resistance. This task is now more feasible due to the increasing availability of bacterial genomic data at or near the point of care. These resources create an opportunity to envision how integration of bacterial genetic determinants of antibiotic response into treatment algorithms might transform TB care. Historically, Mtb drug resistance studies focused on mutations in genes encoding antibiotic targets and the resulting increases in the minimal inhibitory concentrations (MICs) above a breakpoint value. But recent progress in elucidating the effects of functional genetic diversity in Mtb has revealed various genetic loci that are associated with drug phenotypes such as low-level MIC increases and tolerance which predict the development of resistance and treatment failure. As a result, we are now poised to advance precision medicine approaches in TB treatment. By incorporating information regarding Mtb genetic characteristics into the development of drug regimens, clinical care which tailors antibiotic treatment to maximize the likelihood of success has come into reach.

Drug resistant tuberculosis: Implications for transmission, diagnosis, and disease management

Drug resistant tuberculosis contributes significantly to the global burden of antimicrobial resistance, often consuming a large proportion of the healthcare budget and associated resources in many endemic countries. The rapid emergence of resistance to newer tuberculosis therapies signals the need to ensure appropriate antibiotic stewardship, together with a concerted drive to develop new regimens that are active against currently circulating drug resistant strains. Herein, we highlight that the current burden of drug resistant tuberculosis is driven by a combination of ongoing transmission and the intra-patient evolution of resistance through several mechanisms. Global control of tuberculosis will require interventions that effectively address these and related aspects. Interrupting tuberculosis transmission is dependent on the availability of novel rapid diagnostics which provide accurate results, as near-patient as is possible, together with appropriate linkage to care. Contact tracing, longitudinal follow-up for symptoms and active mapping of social contacts are essential elements to curb further community-wide spread of drug resistant strains. Appropriate prophylaxis for contacts of drug resistant index cases is imperative to limit disease progression and subsequent transmission. Preventing the evolution of drug resistant strains will require the development of shorter regimens that rapidly eliminate all populations of mycobacteria, whilst concurrently limiting bacterial metabolic processes that drive drug tolerance, mutagenesis and the ultimate emergence of resistance. Drug discovery programs that specifically target bacterial genetic determinants associated with these processes will be paramount to tuberculosis eradication. In addition, the development of appropriate clinical endpoints that quantify drug tolerant organisms in sputum, such as differentially culturable/detectable tubercle bacteria is necessary to accurately assess the potential of new therapies to effectively shorten treatment duration. When combined, this holistic approach to addressing the critical problems associated with drug resistance will support delivery of quality care to patients suffering from tuberculosis and bolster efforts to eradicate this disease.

Whole Genome Sequencing Assessing Impact of Diabetes Mellitus on Tuberculosis Mutations and Type of Recurrence in India

BACKGROUND

Evidence describing the impact of diabetes mellitus (DM) on the recurrence and mutation rate of Mycobacterium tuberculosis (Mtb) is limited.

METHODS

This study was nested in 3 cohort studies of tuberculosis (TB) patients with and without DM in India. Paired Mtb isolates recovered at baseline and treatment failure/recurrence underwent whole genome sequencing. We compared acquisition of single-nucleotide polymorphisms (SNPs), TB drug resistance mutations, and type of recurrence (endogenous reactivation [<8 SNPs] or exogenous reinfection [≥8 SNPs]) by DM status.

RESULTS

Of 1633 enrolled in the 3 parent cohorts, 236 (14.5%) had microbiologically confirmed TB treatment failure/recurrence; 76 Mtb isolate pairs were available for sequencing (22 in TB-DM and 54 in TB-only). The SNP acquisition rate was overall was 0.43 (95% confidence interval [CI], .25-.64) per 1 person-year (PY); 0.77 (95% CI, .40-1.35) per 1 PY, and 0.44 (95% CI, .19-.86) per 1 PY at treatment failure and recurrence, respectively. Significant difference in SNP rates by DM status was seen at recurrence (0.21 [95% CI, .04-.61]) per 1 PY for TB-only vs 1.28 (95% CI, .41-2.98) per 1 PY for TB-DM; P = .02). No significant difference in SNP rates by DM status was observed at treatment failure. Acquired TB drug resistance was seen in 4 of 18 (22%) in TB-DM vs 4 of 45 (9%) in TB-only (P = .21). Thirteen (17%) participants had exogenous reinfection; the reinfection rate at recurrence was 25% (3/12) for TB-DM vs 17% (4/24) in TB-only (P = .66).

CONCLUSIONS

Considerable intrahost Mtb mutation rates were present at recurrence among patients with DM in India. One-fourth of patients with DM had exogenous reinfection at recurrence.

Transcontinental spread and evolution of Mycobacterium tuberculosis W148 European/Russian clade toward extensively drug resistant tuberculosis

Transmission-driven multi-/extensively drug resistant (M/XDR) tuberculosis (TB) is the largest single contributor to human mortality due to antimicrobial resistance. A few major clades of the Mycobacterium tuberculosis complex belonging to lineage 2, responsible for high prevalence of MDR-TB in Eurasia, show outstanding transnational distributions. Here, we determined factors underlying the emergence and epidemic spread of the W148 clade by genome sequencing and Bayesian demogenetic analyses of 720 isolates from 23 countries. We dated a common ancestor around 1963 and identified two successive epidemic expansions in the late 1980s and late 1990s, coinciding with major socio-economic changes in the post-Soviet Era. These population expansions favored accumulation of resistance mutations to up to 11 anti-TB drugs, with MDR evolving toward additional resistances to fluoroquinolones and second-line injectable drugs within 20 years on average. Timescaled haplotypic density analysis revealed that widespread acquisition of compensatory mutations was associated with transmission success of XDR strains. Virtually all W148 strains harbored a hypervirulence-associated ppe38 gene locus, and incipient recurrent emergence of prpR mutation-mediated drug tolerance was detected. The outstanding genetic arsenal of this geographically widespread M/XDR strain clade represents a “perfect storm” that jeopardizes the successful introduction of new anti-M/XDR-TB antibiotic regimens.

An outbreak of the multidrug-resistant Mycobacterium tuberculosis lineage W148 has spread widely across Russia, Central Asia and Europe. Here, the authors use whole genome sequences of ~700 isolates of this lineage collected over ~20 years to analyze its spread, evolution of drug resistance, and impact of compensatory mutations.

High fluoroquinolone resistance proportions among multidrug-resistant tuberculosis driven by dominant L2 Mycobacterium tuberculosis clones in the Mumbai Metropolitan Region

Background

Multidrug-resistant (MDR) Mycobacterium tuberculosis complex (MTBC) strains are a serious health problem in India, also contributing to one-fourth of the global MDR tuberculosis (TB) burden. About 36% of the MDR MTBC strains are reported fluoroquinolone (FQ) resistant leading to high pre-extensively drug-resistant (pre-XDR) and XDR-TB (further resistance against bedaquiline and/or linezolid) rates. Still, factors driving the MDR/pre-XDR epidemic in India are not well defined.

Methods

In a retrospective study, we analyzed 1852 consecutive MTBC strains obtained from patients from a tertiary care hospital laboratory in Mumbai by whole genome sequencing (WGS). Univariate and multivariate statistics was used to investigate factors associated with pre-XDR. Core genome multi locus sequence typing, time scaled haplotypic density (THD) method and homoplasy analysis were used to analyze epidemiological success, and positive selection in different strain groups, respectively.

Results

In total, 1016 MTBC strains were MDR, out of which 703 (69.2%) were pre-XDR and 45 (4.4%) were XDR. Cluster rates were high among MDR (57.8%) and pre-XDR/XDR (79%) strains with three dominant L2 (Beijing) strain clusters (Cl 1–3) representing half of the pre-XDR and 40% of the XDR-TB cases. L2 strains were associated with pre-XDR/XDR-TB (P < 0.001) and, particularly Cl 1–3 strains, had high first-line and FQ resistance rates (81.6–90.6%). Epidemic success analysis using THD showed that L2 strains outperformed L1, L3, and L4 strains in short- and long-term time scales. More importantly, L2 MDR and MDR + strains had higher THD success indices than their not-MDR counterparts. Overall, compensatory mutation rates were highest in L2 strains and positive selection was detected in genes of L2 strains associated with drug tolerance (prpB and ppsA) and virulence (Rv2828c). Compensatory mutations in L2 strains were associated with a threefold increase of THD indices, suggesting improved transmissibility.

Conclusions

Our data indicate a drastic increase of FQ resistance, as well as emerging bedaquiline resistance which endangers the success of newly endorsed MDR-TB treatment regimens. Rapid changes in treatment and control strategies are required to contain transmission of highly successful pre-XDR L2 strains in the Mumbai Metropolitan region but presumably also India-wide.

Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations

A general method to infer both positive and purifying selection during the real-time evolution of hypermutator pathogens would be broadly useful. To this end, we introduce a Simple Test to Infer Mode of Selection (STIMS) from metagenomic time series of evolving microbial populations. We test STIMS on metagenomic data generated by simulations of bacterial evolution, and on metagenomic data spanning 62,750 generations of Lenski’s long-term evolution experiment with Escherichia coli (LTEE). This benchmarking shows that STIMS detects positive selection in both nonmutator and hypermutator populations, and purifying selection in hypermutator populations. Using STIMS, we find strong evidence of ongoing positive selection on key regulators of the E. coli gene regulatory network, even in some hypermutator populations. STIMS also detects positive selection on regulatory genes in hypermutator populations of Pseudomonas aeruginosa that adapted to subinhibitory concentrations of colistin–an antibiotic of last resort–for just twenty-six days of laboratory evolution. Our results show that the fine-tuning of gene regulatory networks is a general mechanism for rapid and ongoing adaptation. The simplicity of STIMS, together with its intuitive visual interpretation, make it a useful test for positive and purifying selection in metagenomic data sets that track microbial evolution in real-time.

Organisms often evolve elevated mutation rates as they adapt to new environments. That said, the genomic basis of adaptation in asexual hypermutator populations has been difficult to discern, because the few mutations driving adaptation are often associated with large numbers of non-adaptive “hitchhiker” mutations elsewhere in the genome. To address this research gap, we present a Simple Test to Infer Mode of Selection (STIMS) which aggregates the overall signature of selection seen over hundreds of genes. Using STIMS, we find strong positive selection on key regulators of the E. coli gene regulatory network across nonmutator and hypermutator populations of Lenski’s long-term evolution experiment with Escherichia coli. We also find positive selection on regulatory genes in populations of Pseudomonas aeruginosa that evolved hypermutability as they evolved to resist colistin, an antibiotic of last resort. Our work shows that positive and purifying selection can be resolved in hypermutator populations, given sufficient genomic data, and show that regulatory mutations are a major driver of adaptation in experimental populations of microbes.

Portable sequencing of Mycobacterium tuberculosis for clinical and epidemiological applications

With >1 million associated deaths in 2020, human tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis remains one of the deadliest infectious diseases. A plethora of genomic tools and bioinformatics pipelines have become available in recent years to assist the whole genome sequencing of M. tuberculosis. The Oxford Nanopore Technologies (ONT) portable sequencer is a promising platform for cost-effective application in clinics, including personalizing treatment through detection of drug resistance-associated mutations, or in the field, to assist epidemiological and transmission investigations. In this study, we performed a comparison of 10 clinical isolates with DNA sequenced on both long-read ONT and (gold standard) short-read Illumina HiSeq platforms. Our analysis demonstrates the robustness of the ONT variant calling for single nucleotide polymorphisms, despite the high error rate. Moreover, because of improved coverage in repetitive regions where short sequencing reads fail to align accurately, ONT data analysis can incorporate additional regions of the genome usually excluded (e.g. pe/ppe genes). The resulting extra resolution can improve the characterization of transmission clusters and dynamics based on inferring closely related isolates. High concordance in variants in loci associated with drug resistance supports its use for the rapid detection of resistant mutations. Overall, ONT sequencing is a promising tool for TB genomic investigations, particularly to inform clinical and surveillance decision-making to reduce the disease burden.

CT and 18F-FDG PET abnormalities in contacts with recent tuberculosis infections but negative chest X-ray

Close contacts of individuals with pulmonary tuberculosis are at risk for tuberculosis infection and the development of active tuberculosis. In current contact investigations, immunologic tests (the tuberculin skin test and interferon-gamma release assay) and chest X-ray examinations are used to dichotomize contacts with Mycobacterium tuberculosis infections into those with active (X-ray abnormalities) versus latent tuberculosis (normal radiographs). This article is a critical review of computed tomographic (CT) and 18-fluorodeoxyglucose positron emission tomographic (PET) findings of incipient tuberculosis without X-ray abnormalities based on a systematic literature review of twenty-five publications. The CT and 18-fluorodeoxyglucose PET studies revealed minimal pauci-nodular infiltrations in the lung parenchyma and mediastinal lymph nodes abnormalities with metabolic uptake in approximately one-third of asymptomatic close contacts with negative chest radiographic and bacteriological/molecular results for active tuberculosis. Tuberculosis with minimal changes challenge the validity of simply dichotomizing cases of recent M. tuberculosis infections in contacts depending on the presence of X-ray abnormalities as the recent infections may spontaneously regress, remain stagnant, or progress to active tuberculosis in human and nonhuman primate studies. Whether contacts with tuberculosis with minimal changes are interpreted as having active tuberculosis or latent tuberculosis has clinical implications in terms of specific benefits and harms under the current contact management. Advanced imaging tools may help further stratify contacts intensely exposed to M. tuberculosis on a continuous spectrum from latent tuberculosis to incipient, subclinical and active tuberculosis. Identifying incipient tuberculosis would provide an opportunity for earlier and tailored treatment before active tuberculosis is established.

Molecular Surveillance of Antimicrobial Resistance of Mycobacterium leprae from Leprosy Patients in Zhejiang Province, China

Purpose

Reports on antimicrobial resistance (AMR) of Mycobacterium leprae (M. leprae) in Zhejiang Province are limited. Thus, this study aimed to investigate the drug resistance of new leprosy cases within several years and analyse the emergence of AMR mutations from Zhejiang Province.

Methods

This study enrolled 34 leprosy cases in Zhejiang Province, China, from 2018 to 2021. Gene mutation of WHO-recommended DRDRs (folP1, rpoB and gyrA) and genes of compensatory AMR-associated DRDRs, including nth, rpoA, rpoC, gyrB and 23S rRNA, were detected by amplification. Clinical data analysis was performed to investigate the epidemiological association of leprosy.

Results

Of the 34 samples, 2 (5.9%) strains showed drug resistance, which were mutated to dapsone and ofloxacin, separately. Two single mutations in gyrB were detected in different strains (5.9%), whereas one of the rpoC mutation was also detected in one strain each (2.9%), which were proved to be polymorphs. No correlation of drug resistance proportion was identified in male vs female, nerve vs no nerve involvement, deformity vs no deformity and reaction vs non-reaction cases.

Conclusion

Results showed well control of leprosy patients in Zhejiang Province. Gene mutations of WHO-recommended DRDRs folP1 and gyrA confirmed the resistance to dapsone and ofloxacin. Compensatory AMR-associated mutations confirmed to be polymorphs still require further study to determine their phenotypic outcomes in M. leprae. The results demonstrated that drug-resistant strains are not epidemic in this area. Given the few cases of leprosy, analysing the AMR of M. leprae in Zhejiang Province more comprehensively is difficult. However, regular MDT treatment and population management in the early stage may contribute to the low prevalence of leprosy.

Hairpin Structure Facilitates Multiplex High-Fidelity DNA Amplification in Real-Time Polymerase Chain Reaction

Clinically and biologically, it is essential to detect rare DNA-sequence variants for early cancer diagnosis or drug-resistance mutation identification. Some of the common quantitative polymerase chain reaction (qPCR)-based variant detection methods are restricted in the limit of detection (LoD) because the DNA polymerases used for these methods have a high polymerase misincorporation rate; thus, the detection sensitivity is sometimes unsatisfactory. With the proofreading activity, high-fidelity (HiFi) DNA polymerases have a 50- to 250-fold higher fidelity. However, there are currently no proper probe-based designs functioning as the fluorescence indicator allowing multiplexed HiFi qPCR reactions, thus restricting the application of HiFi DNA polymerases like the variant detection. We presented the occlusion system, composed of a 5'-overhanged primer with a fluorophore modification and a probe with a short-stem hairpin and a 3' quencher modification. We demonstrated that the occlusion system allowed multiplexing HiFi qPCR reaction, and it was compatible with the current variant-enrichment method to improve the LoD up to 10-fold. Thus, the occlusion system satisfactorily functioned as an efficient fluorescence indicator in HiFi qPCR reactions and allowed the application of HiFi DNA polymerases in variant detection methods to improve detection sensitivity.

Molecular characteristics of Mycobacterium tuberculosis drug-resistant isolates from HIV- and HIV+ tuberculosis patients in Russia

Background

High burden of drug-resistant (DR) tuberculosis (TB) is a significant threat to national TB control programs all over the world and in the Russian Federation. Different Mycobacterium tuberculosis (MTB) genotypes are hypothesized to have specific characteristics affecting TB control programs. For example, Beijing strains are supposed to have higher mutation rates compared to strains of other genotypes and subsequently higher capability to develop drug-resistance.

Results

Clinical MTB isolates from HIV- and HIV+ patients from four regions of Russia were analyzed for genotypes and mutations conferring resistance to Isoniazid, Rifampicin, Ethambutol, aminoglycosides, and fluoroquinolones. Analysis of genotypes and polymorphism of genomic loci according to the HIV status of the patients – sources of MTB isolates were performed. Studied MTB isolates from HIV- TB patients belonged to 15 genotypes and from HIV + TB patients – to 6 genotypes. Beijing clinical isolates dominated in HIV- (64,7%) and HIV+ (74,4%) groups. Other isolates were of LAM (including LAM1 and LAM9), Ural, and 4 minor groups of genotypes (including 5 subclones T). The spectrum of genotypes in the HIV- group was broader than in the HIV+ group. PR of B0/W148 Beijing was significantly lower than of other Beijing genotypes in susceptible and MDR-XDR isolates. Rates of isolates belonging to non-Beijing genotypes were higher than Beijing in susceptible isolates from HIV- patients.

Conclusions

Beijing genotype isolates prevailed in clinical isolates of all drug susceptibility profiles both from HIV- and HIV+ patients, although B0/W148 Beijing genotype did not dominate in this study. Genome loci and mutations polymorphisms were more pronounced in clinical isolates from HIV- patients, than from HIV+.

Evolution and spread of a highly drug resistant strain of Mycobacterium tuberculosis in Papua New Guinea

BACKGROUND

Molecular mechanisms determining the transmission and prevalence of drug resistant tuberculosis (DR-TB) in Papua New Guinea (PNG) are poorly understood. We used genomic and drug susceptibility data to explore the evolutionary history, temporal acquisition of resistance and transmission dynamics of DR-TB across PNG.

METHODS

We performed whole genome sequencing on isolates from Central Public Health Laboratory, PNG, collected 2017-2019. Data analysis was done on a composite dataset that also included 100 genomes previously sequenced from Daru, PNG (2012-2015).

RESULTS

Sampled isolates represented 14 of the 22 PNG provinces, the majority (66/94; 70%) came from the National Capital District (NCD). In the composite dataset, 91% of strains were Beijing 2.2.1.1, identified in 13 provinces. Phylogenetic tree of Beijing strains revealed two clades, Daru dominant clade (A) and NCD dominant clade (B). Multi-drug resistance (MDR) was repeatedly and independently acquired, with the first MDR cases in both clades noted to have emerged in the early 1990s, while fluoroquinolone resistance emerged in 2009 (95% highest posterior density 2000-2016). We identified the presence of a frameshift mutation within Rv0678 (p.Asp47fs) which has been suggested to confer resistance to bedaquiline, despite no known exposure to the drug. Overall genomic clustering was significantly associated with rpoC compensatory and inhA promoter mutations (p < 0.001), with high percentage of most genomic clusters (12/14) identified in NCD, reflecting its role as a potential national amplifier.

CONCLUSIONS

The acquisition and evolution of drug resistance among the major clades of Beijing strain threaten the success of DR-TB treatment in PNG. With continued transmission of this strain in PNG, genotypic drug resistance surveillance using whole genome sequencing is essential for improved public health response to outbreaks. With occurrence of resistance to newer drugs such as bedaquiline, knowledge of full drug resistance profiles will be important for optimal treatment selection.