Phylogeography and transmission of M. tuberculosis in Moldova: A prospective genomic analysis

Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review

Tuberculosis remains a leading cause of infection-related mortality, and efforts to reduce its incidence have been hindered by an incomplete understanding of local Mycobacterium tuberculosis transmission dynamics. Advances in pathogen sequencing and spatial analysis have created new opportunities to map M tuberculosis transmission patterns more precisely. In this scoping review, we searched for studies combining pathogen genetics and location data to analyse the spatial patterns of M tuberculosis transmission and identified 142 studies published between 1994 and 2024. Secular changes in genetic methods were observed, with genome sequencing approaches largely replacing lower-resolution genotyping methods since 2020. The included studies addressed four primary research questions: how are tuberculosis cases and M tuberculosis transmission clusters geographically distributed; do spatially concentrated M tuberculosis clusters exist, and where are these areas located; when spatial concentration occurs, what host, pathogen, or environmental factors contribute to these patterns; and do identifiable relationships exist between the spatial proximity of tuberculosis cases and the genetic similarity of the M tuberculosis isolates infecting these individuals? Collectively, in this Review, we examined the available study data, evaluated the analytical requirements for addressing these questions, and discussed opportunities and challenges for future research. We found that the integration of spatial and genomic data can inform a detailed understanding of local M tuberculosis transmission patterns, but improved study designs and new analytical methods to address gaps in sampling completeness and to integrate additional movement data are needed to fully realise the potential of these tools.

Distribution and transmission of M. tuberculosis in a high-HIV prevalence city in Malawi: A genomic and spatial analysis

Delays in identifying and treating individuals with infectious tuberculosis (TB) contribute to poor health outcomes and allow ongoing community transmission of M. tuberculosis (Mtb). Current recommendations for screening for tuberculosis specify community characteristics (e.g., areas with high local tuberculosis prevalence) that can be used to target screening within the general population. However, areas of higher tuberculosis burden are not necessarily areas with higher rates of transmission. We investigated the transmission of Mtb using high-resolution surveillance data in Blantyre, Malawi. We extracted and performed whole genome sequencing on mycobacterial DNA from cultured M. tuberculosis isolates obtained from culture-positive tuberculosis cases at the time of tuberculosis (TB) notification in Blantyre, Malawi between 2015-2019. We constructed putative transmission networks identified using TransPhylo and investigated individual and pair-wise demographic, clinical, and spatial factors associated with person-to-person transmission. We found that 56% of individuals with sequenced isolates had a probable transmission link to at least one other individual in the study. We identified thirteen putative transmission networks that included five or more individuals. Five of these networks had a single spatial focus of transmission in the city, and each focus centered in a distinct neighborhood in the city. We also found that approximately two-thirds of inferred transmission links occurred between individuals residing in different geographic zones of the city. While the majority of detected tuberculosis transmission events in Blantyre occurred between people living in different zones, there was evidence of distinct geographical concentration for five transmission networks. These findings suggest that targeted interventions in areas with evidence of localized transmission may be an effective local tactic, but will likely need to be augmented by city-wide interventions to improve case finding to have sustained impact.

A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission

BACKGROUND

Mixed infection with multiple strains of the same pathogen in a single host can present clinical and analytical challenges. Whole genome sequence (WGS) data can identify signals of multiple strains in samples, though the precision of previous methods can be improved. Here, we present MixInfect2, a new tool to accurately detect mixed samples from Mycobacterium tuberculosis short-read WGS data. We then evaluate three approaches for reconstructing the underlying mixed constituent strain sequences. This allows these samples to be included in downstream analysis to gain insights into the epidemiology and transmission of mixed infections.

METHODS

We employed a Gaussian mixture model to cluster allele frequencies at mixed sites (hSNPs) in each sample to identify signals of multiple strains. Building upon our previous tool, MixInfect, we increased the accuracy of classifying in vitro mixed samples through multiple improvements to the bioinformatic pipeline. Major and minor proportion constituent strains were reconstructed using three approaches and assessed by comparing the estimated sequence to the known constituent strain sequence. Lastly, mixed infections in a real-world Mycobacterium tuberculosis population from Moldova were detected with MixInfect2 and clusters of recent transmission that included major and minor constituent strains were built.

RESULTS

All 36/36 in vitro mixed and 12/12 non-mixed samples were correctly classified with MixInfect2, and major strain proportions were estimated with high accuracy (within 3% of the true strain proportion), outperforming previous tools. Reconstructed major strain sequences closely matched the true constituent sequence by taking the allele at the highest frequency at hSNPs, while the best-performing approach to reconstruct the minor proportion strain sequence was identifying the closest non-mixed isolate in the same population, though no approach was effective when the minor strain proportion was at 5%. Finally, fewer mixed infections were identified in Moldova than previous estimates (6.6% vs 17.4%) and we found multiple instances where the constituent strains of mixed samples were present in transmission clusters.

CONCLUSIONS

MixInfect2 accurately detects samples with evidence of mixed infection from short-read WGS data and provides an excellent estimate of the mixture proportions. While there are limitations in reconstructing the constituent strain sequences of mixed samples, we present recommendations for the best approach to include these isolates in further analyses.

Tiled Amplicon Sequencing Enables Culture-free Whole-Genome Sequencing of Pathogenic Bacteria From Clinical Specimens

Pathogen sequencing is an important tool for disease surveillance and demonstrated its high value during the COVID-19 pandemic. Viral sequencing during the pandemic allowed us to track disease spread, quickly identify new variants, and guide the development of vaccines. Tiled amplicon sequencing, in which a panel of primers is used for multiplex amplification of fragments across an entire genome, was the cornerstone of SARS-CoV-2 sequencing. The speed, reliability, and cost-effectiveness of this method led to its implementation in academic and public health laboratories across the world and adaptation to a broad range of viral pathogens. However, similar methods are not available for larger bacterial genomes, for which whole-genome sequencing typically requires in vitro culture. This increases costs, error rates and turnaround times. The need to culture poses particular problems for medically important bacteria such as Mycobacterium tuberculosis, which are slow to grow and challenging to culture. As a proof of concept, we developed two novel whole-genome amplicon panels for M. tuberculosis and Streptococcus pneumoniae. Applying our amplicon panels to clinical samples, we show the ability to classify pathogen subgroups and to reliably identify markers of drug resistance without culturing. Development of this work in clinical settings has the potential to dramatically reduce the time of diagnosis of drug resistance for multiple drugs in parallel, enabling earlier intervention for high priority pathogens.

TGV: suite of tools to visualize transmission graphs

Graph structures are often used to visualize transmission networks generated using genomic epidemiological methods. However, tools to interactively visualize these graphs do not exist. A browser-based tool allowing users to load and interactively visualize transmission graphs was developed in JavaScript. Associated metadata can be loaded and used to annotate and filter the nodes and edges of transmission networks. The tool is available at jodyphelan.github.io/tgv.

Transmission dynamics of tuberculosis in a high-burden area of China: An 8-year population-based study using whole genome sequencing

OBJECTIVES

This study investigated the transmission patterns of tuberculosis (TB) and its associated risk factors in Hunan province to inform the development of prevention and control strategies in the region.

METHODS

An 8-year retrospective population-based genomic epidemiological study was conducted. Genomic clusters were defined using distance thresholds of 12-single-nucletide-polymorphisms. Risk factors associated with TB transmission were analyzed using logistic regression model. Kernel Density analysis was used to locate hotspots where transmission occurred.

RESULTS

Among 2649 TB cases included in this study, 275 clusters were identified, with an overall clustering rate of 24.7% (654/2649). Nearly 95% (620/654) of clustered strains were isolated from the same county. Of the 275 clusters, 23 (8.4%, 23/275) had differences in drug-resistant profiles, with FQs resistance mutations occurring most frequently (52.2%, 12/23). Multivariate analysis identified male TB patients, those aged 30-60 years, ethnic minorities, nonfarmers, retreated TB patients, and individuals infected with MDR/RR-TB as independent risk factors for TB transmission (P < 0.05). Kernel density analysis showed that among the 5 drug-resistant surveillance sites, Leiyang had the highest clustering rate, followed by Yongshun, Qidong, Hecheng, and Taojiang.

CONCLUSION

Recent transmission in the region is predominantly occurring within counties. The risk factors related to TB transmission and the hotspots where transmission occurs can provide a scientific basis for the formulation of targeted TB prevention and control strategies.

An overview of next generation sequencing strategies and genomics tools used for tuberculosis research

Tuberculosis (TB) is a grave public health concern and is considered the foremost contributor to human mortality resulting from infectious disease. Due to the stringent clonality and extremely restricted genomic diversity, conventional methods prove inefficient for in-depth exploration of minor genomic variations and the evolutionary dynamics operating in Mycobacterium tuberculosis (M.tb) populations. Until now, the majority of reviews have primarily focused on delineating the application of whole-genome sequencing (WGS) in predicting antibiotic resistant genes, surveillance of drug resistance strains, and M.tb lineage classifications. Despite the growing use of next generation sequencing (NGS) and WGS analysis in TB research, there are limited studies that provide a comprehensive summary of there role in studying macroevolution, minor genetic variations, assessing mixed TB infections, and tracking transmission networks at an individual level. This highlights the need for systematic effort to fully explore the potential of WGS and its associated tools in advancing our understanding of TB epidemiology and disease transmission. We delve into the recent bioinformatics pipelines and NGS strategies that leverage various genetic features and simultaneous exploration of host-pathogen protein expression profile to decipher the genetic heterogeneity and host-pathogen interaction dynamics of the M.tb infections. This review highlights the potential benefits and limitations of NGS and bioinformatics tools and discusses their role in TB detection and epidemiology. Overall, this review could be a valuable resource for researchers and clinicians interested in NGS-based approaches in TB research.

Impact and cost-effectiveness of the 6-month BPaLM regimen for rifampicin-resistant tuberculosis in Moldova: A mathematical modeling analysis

BACKGROUND

Emerging evidence suggests that shortened, simplified treatment regimens for rifampicin-resistant tuberculosis (RR-TB) can achieve comparable end-of-treatment (EOT) outcomes to longer regimens. We compared a 6-month regimen containing bedaquiline, pretomanid, linezolid, and moxifloxacin (BPaLM) to a standard of care strategy using a 9- or 18-month regimen depending on whether fluoroquinolone resistance (FQ-R) was detected on drug susceptibility testing (DST).

METHODS AND FINDINGS

The primary objective was to determine whether 6 months of BPaLM is a cost-effective treatment strategy for RR-TB. We used genomic and demographic data to parameterize a mathematical model estimating long-term health outcomes measured in quality-adjusted life years (QALYs) and lifetime costs in 2022 USD ($) for each treatment strategy for patients 15 years and older diagnosed with pulmonary RR-TB in Moldova, a country with a high burden of TB drug resistance. For each individual, we simulated the natural history of TB and associated treatment outcomes, as well as the process of acquiring resistance to each of 12 anti-TB drugs. Compared to the standard of care, 6 months of BPaLM was cost-effective. This strategy was estimated to reduce lifetime costs by $3,366 (95% UI: [1,465, 5,742] p < 0.001) per individual, with a nonsignificant change in QALYs (-0.06; 95% UI: [-0.49, 0.03] p = 0.790). For those stopping moxifloxacin under the BPaLM regimen, continuing with BPaL plus clofazimine (BPaLC) provided more QALYs at lower cost than continuing with BPaL alone. Strategies based on 6 months of BPaLM had at least a 93% chance of being cost-effective, so long as BPaLC was continued in the event of stopping moxifloxacin. BPaLM for 6 months also reduced the average time spent with TB resistant to amikacin, bedaquiline, clofazimine, cycloserine, moxifloxacin, and pyrazinamide, while it increased the average time spent with TB resistant to delamanid and pretomanid. Sensitivity analyses showed 6 months of BPaLM to be cost-effective across a broad range of values for the relative effectiveness of BPaLM, and the proportion of the cohort with FQ-R. Compared to the standard of care, 6 months of BPaLM would be expected to save Moldova's national TB program budget $7.1 million (95% UI: [1.3 million, 15.4 million] p = 0.002) over the 5-year period from implementation. Our analysis did not account for all possible interactions between specific drugs with regard to treatment outcomes, resistance acquisition, or the consequences of specific types of severe adverse events, nor did we model how the intervention may affect TB transmission dynamics.

CONCLUSIONS

Compared to standard of care, longer regimens, the implementation of the 6-month BPaLM regimen could improve the cost-effectiveness of care for individuals diagnosed with RR-TB, particularly in settings with a high burden of drug-resistant TB. Further research may be warranted to explore the impact and cost-effectiveness of shorter RR-TB regimens across settings with varied drug-resistant TB burdens and national income levels.

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.

Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model

BACKGROUND

Multidrug resistant tuberculosis (MDR-TB) represents a major public health concern in the Republic of Moldova, with an estimated 31% of new and 56% of previously treated TB cases having MDR disease in 2022. A recent genomic epidemiology study of incident TB occurring in 2018 and 2019 found that 92% of MDR-TB was the result of transmission. The MDR phenotype was concentrated among two M. tuberculosis (Mtb) lineages: L2.2.1 (Beijing) and L4.2.1 (Ural).

METHODS

We developed and applied a hierarchical Bayesian multinominal logistic regression model to Mtb genomic, spatial, and epidemiological data collected from all individuals with diagnosed TB in Moldova in 2018 and 2019 to identify locations in which specific Mtb strains are being transmitted. We then used a logistic regression model to estimate locality-level factors associated with local transmission.

FINDINGS

We found differences in the spatial distribution and degree of local concentration of disease due to specific strains of Beijing and Ural lineage Mtb. Foci of transmission for four strains of Beijing lineage Mtb, predominantly of the MDR-TB phenotype, were located in several regions, but largely concentrated in Transnistria. In contrast, transmission of Ural lineage Mtb had less marked patterns of spatial aggregation, with a single strain (also of the MDR phenotype) spatially clustered in southern Transnistria. We found a 30% (95% credible interval 2%-80%) increase in odds of a locality being a transmission cluster for each increase of 100 persons per square kilometer, while higher local tuberculosis incidence and poverty were not associated with a locality being a transmission focus.

INTERPRETATION

Our results identified localities where specific Mtb transmission networks were concentrated and quantified the association between locality-level factors and focal transmission. This analysis revealed Transnistria as the primary area where specific Mtb strains (predominantly of the MDR-TB phenotype) were locally transmitted and suggests that targeted intensified case finding in this region may be an attractive policy option.

FUNDING

Funding for this work was provided by the National Institute of Allergy and Infectious Diseases at the US National Institutes of Health.

The Recent Transmission and Associated Risk Factor of Mycobacterium tuberculosis in Golmud City, China

Background

Tuberculosis (TB) remains a severe public health problem globally, and it is essential to comprehend the transmission pattern to control tuberculosis. Herein, we evaluated the drug-resistant characteristics, recent transmission, and associated risk factors of TB in Golmud, Qinghai, China.

Methods

In this study, we performed a population-based study of patients diagnosed with TB in Golmud from 2013 to 2018. Drug-susceptibility testing and whole-genome sequencing were performed on 133 Mycobacterium tuberculosis strains. The genomic clustering rate was calculated to evaluate the level of recent transmission. Risk factors were identified by logistic regression analysis.

Results

Our results showed that 46.97% (62/132) of strains were phylogenetically clustered and formed into 23 transmission clusters, suggesting a high recent transmission of TB in the area. 12.78% (17/133) strains were multidrug-resistant/rifampicin tuberculosis (MDR/RR-TB), with a high drug-resistant burden. Based on drug resistance gene analysis, we found 23 strains belonging to genotype MDR/RR-TB, where some strains may have borderline mutations. Among these strains, 65.2% (15/23) were found within putative transmission clusters. Additionally, risk factor analysis showed that recent transmission of TB happened more in patients with Tibetan nationality or older age.

Conclusion

Overall our study indicates that the recent transmissions of MTB strains, especially genotypic MDR/RR strains, drive the tuberculosis epidemic in Golmud, which could contribute to developing effective TB prevention and control strategies.

Spatial modeling of Mycobacterium tuberculosis transmission with dyadic genetic relatedness data

Understanding factors that contribute to the increased likelihood of pathogen transmission between two individuals is important for infection control. However, analyzing measures of pathogen relatedness to estimate these associations is complicated due to correlation arising from the presence of the same individual across multiple dyadic outcomes, potential spatial correlation caused by unmeasured transmission dynamics, and the distinctive distributional characteristics of some of the outcomes. We develop two novel hierarchical Bayesian spatial methods for analyzing dyadic pathogen genetic relatedness data, in the form of patristic distances and transmission probabilities, that simultaneously address each of these complications. Using individual-level spatially correlated random effect parameters, we account for multiple sources of correlation between the outcomes as well as other important features of their distribution. Through simulation, we show the limitations of existing approaches in terms of estimating key associations of interest, and the ability of the new methodology to correct for these issues across datasets with different levels of correlation. All methods are applied to Mycobacterium tuberculosis data from the Republic of Moldova, where we identify previously unknown factors associated with disease transmission and, through analysis of the random effect parameters, key individuals, and areas with increased transmission activity. Model comparisons show the importance of the new methodology in this setting. The methods are implemented in the R package GenePair.

Genotypic and phenotypic comparison of drug resistance profiles of clinical multidrug-resistant Mycobacterium tuberculosis isolates using whole genome sequencing in Latvia

BACKGROUND

Multidrug-resistant tuberculosis (MDR-TB) remains a major public health problem in many high tuberculosis (TB) burden countries. Phenotypic drug susceptibility testing (DST) take several weeks or months to result, but line probe assays and Xpert/Rif Ultra assay detect a limited number of resistance conferring gene mutations. Whole genome sequencing (WGS) is an advanced molecular testing method which theoretically can predict the resistance of M. tuberculosis (Mtb) isolates to all anti-TB agents through a single analysis.

METHODS

Here, we aimed to identify the level of concordance between the phenotypic and WGS-based genotypic drug susceptibility (DS) patterns of MDR-TB isolates. Overall, data for 12 anti-TB medications were analyzed.

RESULTS

In total, 63 MDR-TB Mtb isolates were included in the analysis, representing 27.4% of the total number of MDR-TB cases in Latvia in 2012-2014. Among them, five different sublineages were detected, and 2.2.1 (Beijing group) and 4.3.3 (Latin American-Mediterranean group) were the most abundant. There were 100% agreement between phenotypic and genotypic DS pattern for isoniazid, rifampicin, and linezolid. High concordance rate (> 90%) between phenotypic and genotypic DST results was detected for ofloxacin (93.7%), pyrazinamide (93.7%) and streptomycin (95.4%). Phenotypic and genotypic DS patterns were poorly correlated for ethionamide (agreement 56.4%), ethambutol (85.7%), amikacin (82.5%), capreomycin (81.0%), kanamycin (85.4%), and moxifloxacin (77.8%). For capreomycin, resistance conferring mutations were not identified in several phenotypically resistant isolates, and, in contrary, for ethionamide, ethambutol, amikacin, kanamycin, and moxifloxacin the resistance-related mutations were identified in several phenotypically sensitive isolates.

CONCLUSIONS

WGS is a valuable tool for rapid genotypic DST for all anti-TB agents. For isoniazid and rifampicin phenotypic DST potentially can be replaced by genotypic DST based on 100% agreement between the tests. However, discrepant results for other anti-TB agents limit their prescription based solely on WGS data. For clinical decision, at the current level of knowledge, there is a need for combination of genotypic DST with modern, validated phenotypic DST methodologies for those medications which did not showed 100% agreement between the methods.

Transmission and resistome of extremely drug-resistant tuberculosis in Beijing, China: A retrospective population-based epidemiological study

BACKGROUND

In this study, we utilized whole genome sequencing (WGS) of clinical extremely drug-resistant tuberculosis (EDR-TB) strains collected during 2014-2020 in Beijing to detect clustered strains.

METHODS

A retrospective cohort study was conducted by inclusion of EDR-TB patients with positive cultures in Beijing between 2014 and 2020.

RESULTS

A total of 95 EDR-TB patients were included in our analysis. Up on the WGS based genotyping, 94 (94/95, 98.9%) out of 95 were identified as lineage 2 (East Asia). The pairwise genomic distance analysis identified 7 clusters, ranging in size from 2 to 5 isolates. The clustering rate of EDR-TB was 21.1%; while no patients had significantly higher odds of clustering. All isolates harbor rpoB RRDR mutations that confer RIF resistance and katG or inhA promoter mutations that confer INH resistance. Of 95 EDR-TB isolates, a total of 15 mutation types were recorded in the transcriptional regulator mmpR5. In vitro susceptibility testing results revealed that 14 (14/15, 93.3%) out of 15 mutation types were resistant to CFZ; whereas only 3 (3/15, 20.0%) showed resistance to BDQ. Interestingly, 12 isolates harbored mutations within rrl locus, whereas only mutations at positions 2294 and 2296 conferred CLA resistance. Favorable outcomes of EDR-TB patients were positively associated with more effective drugs in the regimes.

CONCLUSION

WGS data demonstrate limited transmission of EDR-TB in this metropolis city. WGS-based drug susceptibility predictions will bring benefits to EDR-TB patients to formulate optimal therapeutic regimens.

Limited Nosocomial Transmission of Drug-Resistant Tuberculosis, Moldova

Applying whole-genome-sequencing, we aimed to detect transmission events of multidrug-resistant/rifampin-resistant strains of Mycobacterium tuberculosis complex at a tuberculosis hospital in Chisinau, Moldova. We recorded ward, room, and bed information for each patient and monitored in-hospital transfers over 1 year. Detailed molecular and patient surveillance revealed only 2 nosocomial transmission events.

Discrepancy in the transmissibility of multidrug-resistant Mycobacterium tuberculosis in urban and rural areas in China

The fitness of multidrug-resistant tuberculosis (MDR-TB) is thought to be an important determinant of a strain's ability to be transmitted and cause outbreaks. Studies in the laboratory have demonstrated that MDR-TB strains have reduced fitness but the relative transmissibility of MDR-TB versus drug-susceptible (DS) TB strains in human populations remains unresolved. We used data on genomic clustering from our previous molecular epidemiological study in Songjiang (2011-2020) and Wusheng (2009-2020), China, to compare the relative transmissibility of MDR-TB versus DS-TB. Genomic clusters were defined with a threshold distance of 12-single-nucleotide-polymorphisms and the risk for MDR-TB clustering was analyzed by logistic regression. In total, 2212 culture-positive pulmonary TB patients were enrolled in Songjiang and 1289 in Wusheng. The clustering rates of MDR-TB and DS-TB strains were 19.4% (20/103) and 26.3% (509/1936), respectively in Songjiang, and 43.9% (29/66) and 26.0% (293/1128) in Wusheng. The risk of MDR-TB clustering was 2.34 (95% CI 1.38-3.94) times higher than DS-TB clustering in Wusheng and 0.64 (95% CI 0.38-1.06) times lower in Songjiang. Neither lineage 2, compensatory mutations nor rpoB S450L were significantly associated with MDR-TB transmission, and katG S315T increased MDR-TB transmission only in Wusheng (OR 5.28, 95% CI 1.42-19.21). MDR-TB was not more transmissible than DS-TB in either Songjiang or Wusheng. It appears that the different transmissibility of MDR-TB in Songjiang and Wusheng is likely due to differences in the quality of the local TB control programs. These results suggest that the most effective way to control MDR-TB is by improving local TB control programs.

Phylogenetic relationships of Mycobacterium tuberculosis isolates in Poland: The emergence of Beijing genotype among multidrug-resistant cases

Introduction

The epidemiological situation of tuberculosis (TB) in Poland urges for its continuous and scrupulous monitoring. The objective of this study was to explore the genetic diversity of multidrug-resistant (MDR) and drug-susceptible (DS) Mycobacterium tuberculosis isolates from Poland with a combination of spoligotyping and high-resolution mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) analysis. The results were placed in the Northern and Eastern Europe context.

Methods

The study included 89 (39 MDR and 50 DS) M. tuberculosis isolates collected from as many patients between 2018 and 2021 in Poland. The analysis was done using spoligotyping, and MIRU-VNTR typing at 24 standard loci. The data were compared to those available on Poland and neighbors and global M. tuberculosis datasets.

Results

The main identified families were Beijing (28.1%) and Haarlem (16.8%) while 34.8% of isolates were in the heterogeneous L4-unclassified group. Although the Beijing family was the most prevalent (61.5%) among MDR-TB cases, it accounted for only 2% of DS isolates. Among foreign-born patients, a higher ratio of MDR isolates were observed when compared with those who Poland-born (64.3% vs. 40%). Furthermore, all patients from the Former Soviet Union (FSU) countries were infected with MDR-TB.

Discussion

Whereas DS M. tuberculosis population in Poland is dominated by L4 isolates, MDR isolates are mostly of the Beijing genotype. The rise in the prevalence of the Beijing isolates in Poland, coupled with high proportion of the Beijing genotype among foreign-born TB patients may reflect an ongoing transmission of this family, imported to Poland mainly from FSU countries.

Epidemiological cluster identification using multiple data sources: an approach using logistic regression

In the management of infectious disease outbreaks, grouping cases into clusters and understanding their underlying epidemiology are fundamental tasks. In genomic epidemiology, clusters are typically identified either using pathogen sequences alone or with sequences in combination with epidemiological data such as location and time of collection. However, it may not be feasible to culture and sequence all pathogen isolates, so sequence data may not be available for all cases. This presents challenges for identifying clusters and understanding epidemiology, because these cases may be important for transmission. Demographic, clinical and location data are likely to be available for unsequenced cases, and comprise partial information about their clustering. Here, we use statistical modelling to assign unsequenced cases to clusters already identified by genomic methods, assuming that a more direct method of linking individuals, such as contact tracing, is not available. We build our model on pairwise similarity between cases to predict whether cases cluster together, in contrast to using individual case data to predict the cases' clusters. We then develop methods that allow us to determine whether a pair of unsequenced cases are likely to cluster together, to group them into their most probable clusters, to identify which are most likely to be members of a specific (known) cluster, and to estimate the true size of a known cluster given a set of unsequenced cases. We apply our method to tuberculosis data from Valencia, Spain. Among other applications, we find that clustering can be predicted successfully using spatial distance between cases and whether nationality is the same. We can identify the correct cluster for an unsequenced case, among 38 possible clusters, with an accuracy of approximately 35 %, higher than both direct multinomial regression (17 %) and random selection (< 5 %).

Phylogeography and transmission of Mycobacterium tuberculosis spanning prisons and surrounding communities in Paraguay

Recent rises in incident tuberculosis (TB) cases in Paraguay and the increasing concentration of TB within prisons highlight the urgency of targeting strategies to interrupt transmission and prevent new infections. However, whether specific cities or carceral institutions play a disproportionate role in transmission remains unknown. We conducted prospective genomic surveillance, sequencing 471 Mycobacterium tuberculosis complex genomes, from inside and outside prisons in Paraguay's two largest urban areas, Asunción and Ciudad del Este, from 2016 to 2021. We found genomic evidence of frequent recent transmission within prisons and transmission linkages spanning prisons and surrounding populations. We identified a signal of frequent M. tuberculosis spread between urban areas and marked recent population size expansion of the three largest genomic transmission clusters. Together, our findings highlight the urgency of strengthening TB control programs to reduce transmission risk within prisons in Paraguay, where incidence was 70 times that outside prisons in 2021.

Whole-genome sequencing to characterize the genetic structure and transmission risk of Mycobacterium tuberculosis in Yichang city of China

Objective

The burden of both general and drug-resistant tuberculosis in rural areas is higher than that in urban areas in China. To characterize the genetic structure and transmission risk of Mycobacterium tuberculosis in rural China, we used whole genome sequencing to analyze clinical strains collected from patients in two counties of Yichang for three consecutive years.

Methods

From 2018 to 2020, sputum samples were collected for cultures from patients with suspected tuberculosis in Yidu and Zigui county, and DNA was extracted from the positive strains for genome sequencing. The online SAM-TB platform was used to identify the genotypes and drug resistance-related mutations of each strain, establish a phylogenetic tree, and calculated the genetic distances between pairwise strains. Twelve single nucleotide polymorphisms (SNPs) were used as thresholds to identify transmission clusters. The risk of related factors was estimated by univariable and multivariable logistic regression.

Results

A total of 161 out of the collected 231 positive strains were enrolled for analysis, excluding non-tuberculous mycobacterium and duplicate strains from the same patient. These strains belonged to Lineage 2 (92, 57.1%) and Lineage 4 (69, 42.9%), respectively. A total of 49 (30.4%) strains were detected with known drug resistance-related mutations, including 6 (3.7%) multidrug-resistant-TB (MDR-TB) strains and 11 (6.8%) RIF-resistant INH-susceptible TB (Rr-TB) strains. Six of the MDR/Rr-TB (35.3%) were also resistant to fluoroquinolones, which made them pre-extensively drug-resistant TB (pre-XDR-TB). There were another seven strains with mono-resistance to fluoroquinolones and one strain with resistance to both INH and fluoroquinolones, making the overall rate of fluoroquinolones resistance 8.7% (14/161). A total of 50 strains (31.1%) were identified as transmission clusters. Patients under 45 years old (adjusted odds ratio 3.46 [95% confidential intervals 1.28-9.35]), treatment-naive patients (6.14 [1.39-27.07]) and patients infected by lineage 4 strains (2.22 [1.00-4.91]) had a higher risk of transmission.

Conclusion

The drug resistance of tuberculosis in rural China, especially to the second-line drug fluoroquinolones, is relatively serious. The standardized treatment for patients and the clinical use of fluoroquinolones warrant attention. At the same time, the recent transmission risk of tuberculosis is high, and rapid diagnosis and treatment management at the primary care needs to be strengthened.

Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics

Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application. Here, we generate a population-based dataset from Valencia region and compare it with available datasets from different TB-burden settings to reveal transmission dynamics heterogeneity and its public health implications. We sequenced the whole genome of 785 Mycobacterium tuberculosis strains and linked genomes to patient epidemiological data. We use a pairwise distance clustering approach and phylodynamic methods to characterize transmission events over the last 150 years, in different TB-burden regions. Our results underscore significant differences in transmission between low-burden TB settings, i.e., clustering in Valencia region is higher (47.4%) than in Oxfordshire (27%), and similar to a high-burden area as Malawi (49.8%). By modeling times of the transmission links, we observed that settings with high transmission rate are associated with decades of uninterrupted transmission, irrespective of burden. Together, our results reveal that burden and transmission are not necessarily linked due to the role of past epidemics in the ongoing TB incidence, and highlight the need for in-depth characterization of transmission dynamics and specifically tailored TB control strategies.

Understanding drivers of phylogenetic clustering and terminal branch lengths distribution in epidemics of Mycobacterium tuberculosis

Detecting factors associated with transmission is important to understand disease epidemics, and to design effective public health measures. Clustering and terminal branch lengths (TBL) analyses are commonly applied to genomic data sets of Mycobacterium tuberculosis (MTB) to identify sub-populations with increased transmission. Here, I used a simulation-based approach to investigate what epidemiological processes influence the results of clustering and TBL analyses, and whether differences in transmission can be detected with these methods. I simulated MTB epidemics with different dynamics (latency, infectious period, transmission rate, basic reproductive number R0, sampling proportion, sampling period, and molecular clock), and found that all considered factors, except for the length of the infectious period, affect the results of clustering and TBL distributions. I show that standard interpretations of this type of analyses ignore two main caveats: (1) clustering results and TBL depend on many factors that have nothing to do with transmission, (2) clustering results and TBL do not tell anything about whether the epidemic is stable, growing, or shrinking, unless all the additional parameters that influence these metrics are known, or assumed identical between sub-populations. An important consequence is that the optimal SNP threshold for clustering depends on the epidemiological conditions, and that sub-populations with different epidemiological characteristics should not be analyzed with the same threshold. Finally, these results suggest that different clustering rates and TBL distributions, that are found consistently between different MTB lineages, are probably due to intrinsic bacterial factors, and do not indicate necessarily differences in transmission or evolutionary success.