Whole genome analysis of Mycobacterium tuberculosis isolates from recurrent episodes of tuberculosis, Finland, 1995-2013

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.

Genetic factors associated with acquired phenotypic drug resistance and its compensatory evolution during tuberculosis treatment

OBJECTIVES

We elucidated the factors, evolution, and compensation of antimicrobial resistance (AMR) in Mycobacterium tuberculosis (MTB) isolates under dual pressure from the intra-host environment and anti-tuberculosis (anti-TB) drugs.

METHODS

This retrospective case-control study included 337 patients with pulmonary tuberculosis from 15 clinics in Tianjin, China, with phenotypic drug susceptibility testing results available for at least two time points between January 1, 2009 and December 31, 2016. Patients in the case group exhibited acquired AMR to isoniazid (INH) or rifampicin (RIF), while those in the control group lacked acquired AMR. The whole-genome sequencing (WGS) was conducted on 149 serial longitudinal MTB isolates from 46 patients who acquired or reversed phenotypic INH/RIF-resistance during treatment. The genetic basis, associated factors, and intra-host evolution of acquired phenotypic INH/RIF-resistance were elucidated using a combined analysis.

RESULTS

Anti-TB interruption duration of ≥30 days showed association with acquired phenotypic INH/RIF resistance (aOR = 2·2, 95% CI, 1·0-5·1) and new rpoB mutations (p = 0·024). The MTB evolution was 1·2 (95% CI, 1·02-1·38) single nucleotide polymorphisms per genome per year under dual pressure from the intra-host environment and anti-TB drugs. AMR-associated mutations occurred before phenotypic AMR appearance in cases with acquired phenotypic INH (10 of 16) and RIF (9 of 22) resistances.

DISCUSSION

Compensatory evolution may promote the fixation of INH/RIF-resistance mutations and affect phenotypic AMR. The TB treatment should be adjusted based on gene sequencing results, especially in persistent culture positivity during treatment, which highlights the clinical importance of WGS in identifying reinfection and AMR acquisition before phenotypic drug susceptibility testing.

Whole-genome sequencing as a tool for studying the microevolution of drug-resistant serial Mycobacterium tuberculosis isolates

Treatment of drug-resistant tuberculosis requires extended use of more toxic and less effective drugs and may result in retreatment cases due to failure, abandonment or disease recurrence. It is therefore important to understand the evolutionary process of drug resistance in Mycobacterium tuberculosis. We here in describe the microevolution of drug resistance in serial isolates from six previously treated patients. Drug resistance was initially investigated through phenotypic methods, followed by genotypic approaches. The use of whole-genome sequencing allowed the identification of mutations in the katG, rpsL and rpoB genes associated with drug resistance, including the detection of rare mutations in katG and mixed populations of strains. Molecular docking simulation studies of the impact of observed mutations on isoniazid binding were also performed. Whole-genome sequencing detected 266 single nucleotide polymorphisms between two isolates obtained from one patient, suggesting a case of exogenous reinfection. In conclusion, sequencing technologies can detect rare mutations related to drug resistance, identify subpopulations of resistant strains, and identify diverse populations of strains due to exogenous reinfection, thus improving tuberculosis control by guiding early implementation of appropriate clinical and therapeutic interventions.

Common Adaptive Strategies Underlie Within-Host Evolution of Bacterial Pathogens

Within-host adaptation is a hallmark of chronic bacterial infections, involving substantial genomic changes. Recent large-scale genomic data from prolonged infections allow the examination of adaptive strategies employed by different pathogens and open the door to investigate whether they converge toward similar strategies. Here, we compiled extensive data of whole-genome sequences of bacterial isolates belonging to miscellaneous species sampled at sequential time points during clinical infections. Analysis of these data revealed that different species share some common adaptive strategies, achieved by mutating various genes. Although the same genes were often mutated in several strains within a species, different genes related to the same pathway, structure, or function were changed in other species utilizing the same adaptive strategy (e.g., mutating flagellar genes). Strategies exploited by various bacterial species were often predicted to be driven by the host immune system, a powerful selective pressure that is not species specific. Remarkably, we find adaptive strategies identified previously within single species to be ubiquitous. Two striking examples are shifts from siderophore-based to heme-based iron scavenging (previously shown for Pseudomonas aeruginosa) and changes in glycerol-phosphate metabolism (previously shown to decrease sensitivity to antibiotics in Mycobacterium tuberculosis). Virulence factors were often adaptively affected in different species, indicating shifts from acute to chronic virulence and virulence attenuation during infection. Our study presents a global view on common within-host adaptive strategies employed by different bacterial species and provides a rich resource for further studying these processes.

Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark

BACKGROUND

Pathogen genomics have become increasingly important in infectious disease epidemiology and public health. The Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) guidelines were developed to outline a minimum set of criteria that should be reported in genomic epidemiology studies to facilitate assessment of study quality. We evaluate such reporting practices, using tuberculosis as an example.

METHODS

For this systematic review, we initially searched MEDLINE, Embase Classic, and Embase on May 3, 2017, using the search terms "tuberculosis" and "genom* sequencing". We updated this initial search on April 23, 2019, and also included a search of bioRxiv at this time. We included studies in English, French, or Spanish that recruited patients with microbiologically confirmed tuberculosis and used whole genome sequencing for typing of strains. Non-human studies, conference abstracts, and literature reviews were excluded. For each included study, the number and proportion of fulfilled STROME-ID criteria were recorded by two reviewers. A comparison of the mean proportion of fulfilled STROME-ID criteria before and after publication of the STROME-ID guidelines (in 2014) was done using a two-tailed t test. Quasi-Poisson regression and tobit regression were used to examine associations between study characteristics and the number and proportion of fulfilled STROME-ID criteria. This study was registered with PROSPERO, CRD42017064395.

FINDINGS

976 titles and abstracts were identified by our primary search, with an additional 16 studies identified in bioRxiv. 114 full texts (published between 2009 and 2019) were eligible for inclusion. The mean proportion of STROME-ID criteria fulfilled was 50% (SD 12; range 16-75). The proportion of criteria fulfilled was similar before and after STROME-ID publication (51% [SD 11] vs 46% [14], p=0·26). The number of criteria reported (among those applicable to all studies) was not associated with impact factor, h-index, country of affiliation of senior author, or sample size of isolates. Similarly, the proportion of criteria fulfilled was not associated with these characteristics, with the exception of a sample size of isolates of 277 or more (the highest quartile). In terms of reproducibility, 100 (88%) studies reported which bioinformatic tools were used, but only 33 (33%) reported corresponding version numbers. Sequencing data were available for 86 (75%) studies.

INTERPRETATION

The reporting of STROME-ID criteria in genomic epidemiology studies of tuberculosis between 2009 and 2019 was low, with implications for assessment of study quality. The considerable proportion of studies without bioinformatics version numbers or sequencing data available highlights a key concern for reproducibility.

Recurrent tuberculosis in patients infected with the predominant Mycobacterium tuberculosis outbreak strain in Denmark. New insights gained through whole genome sequencing

OBJECTIVES

Recurrent tuberculosis (TB) is defined by more than one TB episode per patient and is caused by reinfection with a new M. tuberculosis (Mtb) strain or relapse with the previous strain. In Denmark, a major TB outbreak caused by one specific Mtb genotype "DKC2" is ongoing. Of the 892 patients infected with DKC2 between 1992 and 2014, 32 had recurrent TB with 67 TB episodes in total.

METHODS

The 32 cases were evaluated in terms of number of single-nucleotide polymorphism (SNP) differences and time between episodes derived from whole-genome sequencing data.

RESULTS

For four TB cases, the subsequent episodes could be confirmed as relapse and for one case as reinfection. Eight cases with SNP differences <6, theoretically indicating relapse, could be classified as likely reinfections based on phylogenetic analysis in combination with geographical data. Subsequent TB episodes for the remaining 19 cases could not be classified as relapse or reinfection even though they all had a SNP difference of <6 SNPs.

CONCLUSIONS

In newer studies, investigating recurrent TB with the use of WGS, the number of SNPs has been used to distinguish between relapse and reinfection. The algorithm proposed for this is not valid in the Danish TB outbreak setting as our findings challenge the interpretation of few SNP differences as representing relapse. However, when including phylogenetic analysis and geographical data in the analysis, classification of 13 of the 32 cases were possible.

Classifying recurrent Mycobacterium tuberculosis cases in Georgia using MIRU-VNTR typing

INTRODUCTION

Recurrent tuberculosis (TB) is one of the main challenges in TB control. Genotyping based on Mycobacterial Interspersed Repetitive Units-Variable Tandem Repeats (MIRU-VNTR) has been widely used to differentiate between relapse and reinfection, which are the two main causes of recurrent TB. There is a lack of data regarding the causes of TB recurrence in Georgia, and while differentiating between relapse and reinfection plays a key role in defining appropriate interventions, the required genotyping methodologies have not been implemented. The objective of this study was to implement MIRU-VNTR genotyping at the National Center for Tuberculosis and Lung Diseases (NCTBLD) and differentiate between relapse and reinfection in multidrug resistant (MDR-) TB patients from Tbilisi, Georgia.

METHODS

Recurrent MDR tuberculosis cases from 2014-2016 diagnosed at NCTLD were included in the study when bacterial samples from both episodes were available. Genotyping based on the MIRU-VNTR 24 loci was implemented and used for differentiating between relapse and reinfection. Paired samples showing the same MIRU-VNTR pattern or one locus difference were classified as relapse, while two and more loci differences were treated as reinfection. Exact logistic regression was used to identify predictors of recurrence.

RESULTS

Thirty two MDR-TB patients (64 samples) were included and MIRU-VNTR 24 typing was performed on the corresponding paired samples. Of the 32 patients, 25 (83.3%) were identified as relapse while 5 (16.7%) were due to re-infection. Patients with a history of incarceration were significantly associated with TB reinfection (p< 0.05).

CONCLUSION

Recurrent TB in MDR patients in Georgia are mainly caused by relapse, raising concerns on the efficacy of the TB control program. An association between incarceration and reinfection likely reflects high levels of ongoing TB transmission in prisons, indicating the need for better TB infection control measures in these settings. Our results add to the rationale for implementing genotypic surveillance of TB more broadly to support TB control in Georgia.

Whole genome sequencing provides additional insights into recurrent tuberculosis classified as endogenous reactivation by IS6110 DNA fingerprinting

Recurrent tuberculosis (TB) after successful TB treatment occurs due to endogenous reactivation (relapse) or exogenous reinfection. We revisited the conclusions of relapse in a high TB incidence setting that were drawn on the basis of IS6110 restriction fragment length polymorphism (RFLP) analysis in a large retrospective cohort study in suburban Cape Town, South Africa. Using whole genome sequencing (WGS), we undertook pair-wise genome comparison of Mycobacterium tuberculosis strains cultured from diagnostic sputum samples collected at the index and recurrent TB episode for 25 recurrent TB cases who had been classified as relapse based on identical DNA fingerprint patterns in the earlier study. We found that paired strain genome sequences were identical or showed minimal variant differences in 22 of 25 recurrent TB cases, consistent with relapse. One showed 20 variant differences, suggestive of exogenous reinfection. Two of the 25 had mixed infections, each with the index episode strain detected as the dominant strain at recurrence in one of these patients, the minority strain harboured drug-resistance conferring mutations (rpoB, katG). In conclusion, our study highlights the additional value of WGS for investigating recurrent TB in settings with high infection pressure and closely related circulating strains, where the extent of re- and mixed infection may be underestimated.

Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions

Whole-genome sequencing (WGS) is increasingly used to aid the understanding of pathogen transmission. A first step in analyzing WGS data is usually to define "transmission clusters," sets of cases that are potentially linked by direct transmission. This is often done by including two cases in the same cluster if they are separated by fewer single-nucleotide polymorphisms (SNPs) than a specified threshold. However, there is little agreement as to what an appropriate threshold should be. We propose a probabilistic alternative, suggesting that the key inferential target for transmission clusters is the number of transmissions separating cases. We characterize this by combining the number of SNP differences and the length of time over which those differences have accumulated, using information about case timing, molecular clock, and transmission processes. Our framework has the advantage of allowing for variable mutation rates across the genome and can incorporate other epidemiological data. We use two tuberculosis studies to illustrate the impact of our approach: with British Columbia data by using spatial divisions; with Republic of Moldova data by incorporating antibiotic resistance. Simulation results indicate that our transmission-based method is better in identifying direct transmissions than a SNP threshold, with dissimilarity between clusterings of on average 0.27 bits compared with 0.37 bits for the SNP-threshold method and 0.84 bits for randomly permuted data. These results show that it is likely to outperform the SNP-threshold method where clock rates are variable and sample collection times are spread out. We implement the method in the R package transcluster.

Deciphering Within-Host Microevolution of Mycobacterium tuberculosis through Whole-Genome Sequencing: the Phenotypic Impact and Way Forward

The Mycobacterium tuberculosis genome is more heterogenous and less genetically stable within the host than previously thought. Currently, only limited data exist on the within-host microevolution, diversity, and genetic stability of M. tuberculosis As a direct consequence, our ability to infer M. tuberculosis transmission chains and to understand the full complexity of drug resistance profiles in individual patients is limited. Furthermore, apart from the acquisition of certain drug resistance-conferring mutations, our knowledge on the function of genetic variants that emerge within a host and their phenotypic impact remains scarce. We performed a systematic literature review of whole-genome sequencing studies of serial and parallel isolates to summarize the knowledge on genetic diversity and within-host microevolution of M. tuberculosis We identified genomic loci of within-host emerged variants found across multiple studies and determined their functional relevance. We discuss important remaining knowledge gaps and finally make suggestions on the way forward.

Recurrent tuberculosis in Finland 1995-2013: a clinical and epidemiological cohort study

Background

We investigated the epidemiology and prevalence of potential risk factors of tuberculosis (TB) recurrence in a population-based registry cohort of 8084 TB cases between 1995 and 2013.

Methods

An episode of recurrent TB was defined as a case re-registered in the National Infectious Disease Register at least 360 days from the date of the initial registration. A regression model was used to estimate risk factors for recurrence in the national cohort. To describe the presence of known risk factors for recurrence, patient records of the recurrent cases were reviewed for TB diagnosis confirmation, potential factors affecting the risk of recurrence, the treatment regimens given and the outcomes of the TB episodes preceding the recurrence.

Results

TB registry data included 84 patients, for whom more than 1 TB episode had been registered. After a careful clinical review, 50 recurrent TB cases (0.6%) were identified. The overall incidence of recurrence was 113 cases per 100,000 person-years over a median follow up of 6.1 years. For the first 2 years, the incidence of recurrence was over 200/100000. In multivariate analysis of the national cohort, younger age remained an independent risk factor at all time points, and male gender and pulmonary TB at 18 years of follow-up. Among the 50 recurrent cases, 35 patients (70%) had received adequate treatment for the first episode; in 12 cases (24%) the treating physician and in two cases (4%) the patient had discontinued treatment prematurely. In one case (2%) the treatment outcome could not be assessed.

Conclusions

In Finland, the rate of recurrent TB was low despite no systematic directly observed therapy. The first 2 years after a TB episode had the highest risk for recurrence. Among the recurrent cases, the observed premature discontinuation of treatment in the first episode in nearly one fourth of the recurrent cases calls for improved training of the physicians.