A retrospective genomic analysis of drug-resistant strains of M. tuberculosis in a high-burden setting, with an emphasis on comparative diagnostics and reactivation and reinfection status

Unraveling tuberculosis patient cluster transmission chains: integrating WGS-based network with clinical and epidemiological insights

Background

Tuberculosis remains a global health threat, and the World Health Organization reports a limited reduction in disease incidence rates, including both new and relapse cases. Therefore, studies targeting tuberculosis transmission chains and recurrent episodes are crucial for developing the most effective control measures. Herein, multiple tuberculosis clusters were retrospectively investigated by integrating patients' epidemiological and clinical information with median-joining networks recreated based on whole genome sequencing (WGS) data of Mycobacterium tuberculosis isolates.

Methods

Epidemiologically linked tuberculosis patient clusters were identified during the source case investigation for pediatric tuberculosis patients. Only M. tuberculosis isolate DNA samples with previously determined spoligotypes identical within clusters were subjected to WGS and further median-joining network recreation. Relevant clinical and epidemiological data were obtained from patient medical records.

Results

We investigated 18 clusters comprising 100 active tuberculosis patients 29 of whom were children at the time of diagnosis; nine patients experienced recurrent episodes. M. tuberculosis isolates of studied clusters belonged to Lineages 2 (sub-lineage 2.2.1) and 4 (sub-lineages 4.3.3, 4.1.2.1, 4.8, and 4.2.1), while sub-lineage 4.3.3 (LAM) was the most abundant. Isolates of six clusters were drug-resistant. Within clusters, the maximum genetic distance between closely related isolates was only 5-11 single nucleotide variants (SNVs). Recreated median-joining networks, integrated with patients' diagnoses, specimen collection dates, sputum smear microscopy, and epidemiological investigation results indicated transmission directions within clusters and long periods of latent infection. It also facilitated the identification of potential infection sources for pediatric patients and recurrent active tuberculosis episodes refuting the reactivation possibility despite the small genetic distance of ≤5 SNVs between isolates. However, unidentified active tuberculosis cases within the cluster, the variable mycobacterial mutation rate in dormant and active states, and low M. tuberculosis genetic variability inferred precise transmission chain delineation. In some cases, heterozygous SNVs with an allelic frequency of 10-73% proved valuable in identifying direct transmission events.

Conclusion

The complex approach of integrating tuberculosis cluster WGS-data-based median-joining networks with relevant epidemiological and clinical data proved valuable in delineating epidemiologically linked patient transmission chains and deciphering causes of recurrent tuberculosis episodes within clusters.

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.

CD4+ T cells are homeostatic regulators during Mtb reinfection

Immunological priming - either in the context of prior infection or vaccination - elicits protective responses against subsequent Mycobacterium tuberculosis (Mtb) infection. However, the changes that occur in the lung cellular milieu post-primary Mtb infection and their contributions to protection upon reinfection remain poorly understood. Here, using clinical and microbiological endpoints in a non-human primate reinfection model, we demonstrate that prior Mtb infection elicits a long-lasting protective response against subsequent Mtb exposure and that the depletion of CD4+ T cells prior to Mtb rechallenge significantly abrogates this protection. Leveraging microbiologic, PET-CT, flow cytometric, and single-cell RNA-seq data from primary infection, reinfection, and reinfection-CD4+ T cell depleted granulomas, we identify differential cellular and microbial features of control. The data collectively demonstrate that the presence of CD4+ T cells in the setting of reinfection results in a reduced inflammatory lung milieu characterized by reprogrammed CD8+ T cell activity, reduced neutrophilia, and blunted type-1 immune signaling among myeloid cells, mitigating Mtb disease severity. These results open avenues for developing vaccines and therapeutics that not only target CD4+ and CD8+ T cells, but also modulate innate immune cells to limit Mtb disease.

Strain structure analysis of Mycobacterium tuberculosis circulating among HIV negative, positive and drug resistant TB patients attending chest clinics in Western Kenya

BACKGROUND

Despite global tuberculosis (TB) interventions, the disease remains one of the major public health concerns. Kenya is ranked 15th among 22 high burden TB countries globally.

METHODS

A cross-sectional study was conducted in Western Kenya, which comprises 10 counties. A multistage sampling method was used where a single sub-county was randomly selected followed by sampling two high volume health facility from each sub-county. Identification of spoligotype profiles and their family distribution and lineage level were achieved by comparison with SITVIT database.

RESULTS

Lineage distribution pattern revealed that the most predominant lineage was CAS 220 (39.8%) followed by Beijing 128 (23.1%). The other lineages identified were T, LAM, H, X, S and MANU which were quantified as 87 (15.7%), 67 (12.1%), 16 (2.8%), 10 (1.8%), 8 (1.4%) and 5 (0.9%) respectively. CAS and Beijing strains were the most predominant lineage in both HIV negative and positive TB patients. The Beijing lineage was also the most predominant in resistant M. tuberculosis strains as compared to wild type. A total of 12 (2.0%) were orphaned M. tuberculosis strains which were spread across all the 10 counties of the study site. In multivariate logistic regression adjusting for potential cofounders three potential risk factors were significant. HIV status (OR = 1.52, CI = 0.29-3.68 and P value of 0.001), Alcohol use (OR = 0.59, CI = 0.43-3.12 and P-value =0.001) and cross border travel (OR = 0.61, CI = 0.49-3.87 and P value = 0.026). Most M. tuberculosis clinical isolates showed genetic clustering with multivariate logistic regression indicating three potential risk factors to clustering. HIV status (OR = 1.52, CI = 0.29-3.68 and P value of 0.001), Alcohol use (OR = 0.59, CI = 0.43-3.12 and P-value =0.001) and cross border travel (OR = 0.61, CI = 0.49-3.87 and P value = 0.026).

CONCLUSION

There exist diverse strains of M. tuberculosis across the 10 counties of Western Kenya. Predominant distribution of clustered genotype points to the fact that most TB cases in this region are as a result of resent transmission other than activation of latent TB.

Combining Radiological and Genomic TB Portals Data for Drug Resistance Analysis

Tuberculosis (TB) drug resistance is a worldwide public health problem. It decreases the likelihood of a positive outcome for the individual patient and increases the likelihood of disease spread. Therefore, early detection of TB drug resistance is crucial for improving outcomes and controlling disease transmission. While drug-sensitive tuberculosis cases are declining worldwide because of effective treatment, the threat of drug-resistant tuberculosis is growing, and the success rate of drug-resistant tuberculosis treatment is only around 60%. The TB Portals program provides a publicly accessible repository of TB case data with an emphasis on collecting drug-resistant cases. The dataset includes multi-modal information such as socioeconomic/geographic data, clinical characteristics, pathogen genomics, and radiological features. The program is an international collaboration whose participants are typically under a substantial burden of drug-resistant tuberculosis, with data collected from standard clinical care provided to the patients. Consequentially, the TB Portals dataset is heterogenous in nature, with data representing multiple treatment centers in different countries and containing cross-domain information. This study presents the challenges and methods used to address them when working with this real-world dataset. Our goal was to evaluate whether combining radiological features derived from a chest X-ray of the host and genomic features from the pathogen can potentially improve the identification of the drug susceptibility type, drug-sensitive (DS-TB) or drug-resistant (DR-TB), and the length of the first successful drug regimen. To perform these studies, significantly imbalanced data needed to be processed, which included a much larger number of DR-TB cases than DS-TB, many more cases with radiological findings than genomic ones, and the sparse high dimensional nature of the genomic information. Three evaluation studies were carried out. First, the DR-TB/DS-TB classification model achieved an average accuracy of 92.4% when using genomic features alone or when combining radiological and genomic features. Second, the regression model for the length of the first successful treatment had a relative error of 53.5% using radiological features, 25.6% using genomic features, and 22.0% using both radiological and genomic features. Finally, the relative error of the third regression model predicting the length of the first treatment using the most common drug combination varied depending on the feature type used. When using radiological features alone, the relative error was 17.8%. For genomic features alone, the relative error increased to 19.9%. The model had a relative error of 19.0% when both radiological and genomic features were combined. Although combining radiological and genomic features did not improve upon the use of genomic features when classifying DR-TB/DS-TB, the combination of the two feature types improved the relative error of the predictive model for the length of the first successful treatment. Furthermore, the regression model trained on radiological features achieved the best performance when predicting the treatment length of the most common drug combination.

Tuberculosis reinfection and relapse in eastern China: A prospective study using whole-genome sequencing

OBJECTIVES

Tuberculosis recurrence after an initial successful treatment episode can occur from either reinfection or relapse. In a population-based sample and whole genome sequencing (WGS) in eastern China, we aimed to evaluate risk factors for tuberculosis recurrence, and assess the proportion of recurrence due to either reinfection or relapse.

METHODS

Successfully treated pulmonary tuberculosis patients with sputum culture positive results were recruited from five cities in Jiangsu Province from 2013-2015 and followed for two years for tuberculosis recurrence. Among patients developing a second tuberculosis episode, WGS was performed to distinguish relapse or reinfection through a distance threshold of 6-single-nucleotide polymorphisms (SNP). We analyzed risk factors for recurrence and epidemiological characteristics of different types of recurrent patients.

RESULTS

Of 1,897 successful treated tuberculosis patients, 7.4% (141/1879) developed recurrent tuberculosis. Compared with non-recurrent tuberculosis, patients were at higher risk of recurrence in older age (Adjusted Odds Ratio [AOR], 1.02 for each additional year; 95% CI, 1.01-1.03, P=0.003), patients previously treated for tuberculosis (AOR=2.22; 95% CI, 1.52-3.26, P<0.001), or with bilateral cavities (AOR, 1.56; 95% CI, 1.05-2.32, P=0.029). Among 27.0% (38/141) recurrent tuberculosis patients with successfully sequenced pairs, relapse was substantially more common than reinfection (71.1% versus 28.9%, P=0.014).

CONCLUSIONS

Endogenous relapse was significantly more common than exogenous reinfection in the first two years after treatment in eastern China. Prioritization of high-risk groups for recurrence, such as the elderly, with a previous tuberculosis diagnosis, or with bilateral cavities, may provide opportunities to reduce post-tuberculosis morbidity.

Patterns of genomic interrelatedness of publicly available samples in the TB portals database

The TB Portals program is an international collaboration for the collection and dissemination of tuberculosis data from patient cases focused on drug resistance. The central database is a patient-oriented resource containing both patient and pathogen clinical and genomic information. Herein we provide a summary of the pathogen genomic data available through the TB Portals and show one potential application by examining patterns of genomic pairwise distances. Distributions of pairwise distances highlight overall patterns of genome variability within and between Mycobacterium tuberculosis phylogenomic lineages. Closely related isolates (based on whole-genome pairwise distances and time between sample collection dates) from different countries were identified as potential evidence of international transmission of drug-resistant tuberculosis. These high-level views of genomic relatedness provide information that can stimulate hypotheses for further and more detailed research.

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

BACKGROUND

The incidence of multidrug-resistant tuberculosis (MDR-TB) remains critically high in countries of the former Soviet Union, where >20% of new cases and >50% of previously treated cases have resistance to rifampin and isoniazid. Transmission of resistant strains, as opposed to resistance selected through inadequate treatment of drug-susceptible tuberculosis (TB), is the main driver of incident MDR-TB in these countries.

METHODS AND FINDINGS

We conducted a prospective, genomic analysis of all culture-positive TB cases diagnosed in 2018 and 2019 in the Republic of Moldova. We used phylogenetic methods to identify putative transmission clusters; spatial and demographic data were analyzed to further describe local transmission of Mycobacterium tuberculosis. Of 2,236 participants, 779 (36%) had MDR-TB, of whom 386 (50%) had never been treated previously for TB. Moreover, 92% of multidrug-resistant M. tuberculosis strains belonged to putative transmission clusters. Phylogenetic reconstruction identified 3 large clades that were comprised nearly uniformly of MDR-TB: 2 of these clades were of Beijing lineage, and 1 of Ural lineage, and each had additional distinct clade-specific second-line drug resistance mutations and geographic distributions. Spatial and temporal proximity between pairs of cases within a cluster was associated with greater genomic similarity. Our study lasted for only 2 years, a relatively short duration compared with the natural history of TB, and, thus, the ability to infer the full extent of transmission is limited.

CONCLUSIONS

The MDR-TB epidemic in Moldova is associated with the local transmission of multiple M. tuberculosis strains, including distinct clades of highly drug-resistant M. tuberculosis with varying geographic distributions and drug resistance profiles. This study demonstrates the role of comprehensive genomic surveillance for understanding the transmission of M. tuberculosis and highlights the urgency of interventions to interrupt transmission of highly drug-resistant M. tuberculosis.

Risk factors for types of recurrent tuberculosis (reactivation versus reinfection): A global systematic review and meta-analysis

BACKGROUND

The purpose of this meta-analysis (PROSPERO number: CRD42021243204) is to perform extensive and penetrating analyses on the risk factors associated with reactivation or reinfection.

METHODS

We searched PubMed and Embase using search terms. Risk factors (including sex, length of time between first onset and recurrent diagnosis, extrapulmonary tuberculosis, sputum smear, pulmonary cavity, Beijing family strains, diabetes, HIV infection, history of imprisonment, and immigration) were analyzed. The pooled risk ratio (RR) and 95% confidence interval (CI) were calculated with STATA 15.1. Heterogeneity was evaluated by I² and P values.

RESULTS

The meta-analysis included 25 studies with a total of 1,477 patients. After subgroup analysis, sensitivity analysis, and testing for publication bias, it was concluded that time spanning less than two years (RR=1.56, 95% CI: 1.33-1.85) was a risk factor for endogenous reactivation, while coinfection with HIV (RR=0.72, 95% CI: 0.63-0.83), Beijing family genotype (RR=0.46, 95% CI: 0.32-0.67), history of imprisonment (RR=0.36, 95% CI: 0.16-0.81) and immigration (RR=0.66, 95% CI: 0.53-0.82) were associated with exogenous reinfection.

CONCLUSIONS

The recurrence interval is a risk factor for the endogenous reactivation of tuberculosis. Infection with Beijing family strains, coinfection with HIV, imprisonment, and immigration contribute to the risk of exogenous reinfection.

Highly transmitted M. tuberculosis strains are more likely to evolve MDR/XDR and cause outbreaks, but what makes them highly transmitted?

Multi-Drug-Resistant strains of Mycobacterium tuberculosis (MDR-TB) are a serious obstacle to global TB eradication. While most MDR-TB strains are infrequently transmitted, a few cause large transmission clusters that contribute substantially to local MDR-TB burdens. Here we examine whether the known mutations in these strains can explain their success. Drug resistance mutations differ in fitness costs and strains can also acquire compensatory mutations (CM) to restore fitness, but some highly transmitted MDR strains have no CM. The acquisition of resistance mutations that maintain high transmissibility seems to occur by chance and are more likely in strains that are intrinsically highly transmitted and cause many cases. Modern Beijing lineage strains have caused several large outbreaks, but MDR outbreaks are also caused by ancient Beijing and lineage 4 strains, suggesting the lineage is less important than the characteristics of the individual strain. The development of fluoroquinolone resistance appears to represent another level of selection, in which strains must surmount unknown fitness costs of gyrA mutations. The genetic determinants of high transmission are poorly defined but may involve genes encoding proteins involved in molybdenum acquisition and the Esx systems. In addition, strains eliciting lower cytokine responses and producing more caseating granulomas may have advantages for transmission. Successful MDR/XDR strains generally evolve from highly transmitted drug sensitive parent strains due to selection pressures from deficiencies in local TB control programs. Until TB incidence is considerably reduced, there will likely be highly transmitted strains that develop resistance to any new antibiotic.

Methods for Detecting Mycobacterial Mixed Strain Infections-A Systematic Review

Mixed strain infection (MSI) refers to the concurrent infection of a susceptible host with multiple strains of a single pathogenic species. Known to occur in humans and animals, MSIs deserve special consideration when studying transmission dynamics, evolution, and treatment of mycobacterial diseases, notably tuberculosis in humans and paratuberculosis (or Johne's disease) in ruminants. Therefore, a systematic review was conducted to examine how MSIs are defined in the literature, how widespread the phenomenon is across the host species spectrum, and to document common methods used to detect such infections. Our search strategy identified 121 articles reporting MSIs in both humans and animals, the majority (78.5%) of which involved members of the Mycobacterium tuberculosis complex, while only a few (21.5%) examined non-tuberculous mycobacteria (NTM). In addition, MSIs exist across various host species, but most reports focused on humans due to the extensive amount of work done on tuberculosis. We reviewed the strain typing methods that allowed for MSI detection and found a few that were commonly employed but were associated with specific challenges. Our review notes the need for standardization, as some highly discriminatory methods are not adapted to distinguish between microevolution of one strain and concurrent infection with multiple strains. Further research is also warranted to examine the prevalence of NTM MSIs in both humans and animals. In addition, it is envisioned that the accurate identification and a better understanding of the distribution of MSIs in the future will lead to important information on the epidemiology and pathophysiology of mycobacterial diseases.