Genomic Epidemiology of a Major Mycobacterium tuberculosis Outbreak: Retrospective Cohort Study in a Low-Incidence Setting Using Sparse Time-Series Sampling

The impact of living conditions and health interventions on tuberculosis, Denmark, 1876 to 2022

BackgroundDenmark possesses an exceptional historical data collection on tuberculosis (TB) from 1876 to the present, providing a unique opportunity to assess TB epidemiology over 147 years in Denmark.AimOur aim was to describe the TB disease burden in Denmark in relation to historical events, living conditions and health interventions during the past 147 years.MethodsWe performed a nationwide register-based ecological study including all persons with TB in Denmark from 1876 through 2022, correlating the TB incidence to social, economic and health indicators.ResultsIn Denmark, the overall TB incidence and mortality declined markedly over the past 147 years, only marginally influenced by specific TB interventions such as sanatoria, Bacillus Calmette-Guèrin (BCG) vaccination, mass screenings and antibiotics. Parallel to this decline, the country experienced improved living conditions, as illustrated by decreased infant mortality and increased life expectancy and wealth. In 1978, Denmark became a low-incidence country for TB with risk groups predominantly affected, and with a continuous change in demographics towards fewer Danish-born cases and relatively more migrant cases.ConclusionsThe decline over time in TB incidence and mortality in Denmark preceded specific TB interventions and can, first of all, be attributed to improved living conditions. TB has now become a rare disease in Denmark, predominantly occurring in particular risk groups. Future elimination of TB will require a combination of specific health interventions in these risk groups combined with a continued focus on improving socioeconomic status and living conditions.

Deciphering the Tangible Spatio-Temporal Spread of a 25-Year Tuberculosis Outbreak Boosted by Social Determinants

Outbreak strains of Mycobacterium tuberculosis are promising candidates as targets in the search for intrinsic determinants of transmissibility, as they are responsible for many cases with sustained transmission; however, the use of low-resolution typing methods and restricted geographical investigations represent flaws in assessing the success of long-lived outbreak strains. We can now address the nature of outbreak strains by combining large genomic data sets and phylodynamic approaches. We retrospectively sequenced the whole genome of representative samples assigned to an outbreak circulating in the Canary Islands (the GC strain) since 1993, which accounts for ~20% of local tuberculosis cases. We selected a panel of specific single nucleotide polymorphism (SNP) markers for an in-silico search for additional outbreak-related sequences within publicly available tuberculosis genomic data. Using this information, we inferred the origin, spread, and epidemiological parameters of the GC strain. Our approach allowed us to accurately trace the historical and more recent dispersion of the GC strain. We provide evidence of a highly successful nature within the Canarian archipelago but limited expansion abroad. Estimation of epidemiological parameters from genomic data disagree with a distinctive biology of the GC strain. With the increasing availability of genomic data allowing for the accurate inference of strain spread and critical epidemiological parameters, we can now revisit the link between Mycobacterium tuberculosis genotypes and transmission, as is routinely carried out for SARS-CoV-2 variants of concern. We demonstrate that social determinants rather than intrinsically higher bacterial transmissibility better explain the success of the GC strain. Importantly, our approach can be used to trace and characterize strains of interest worldwide. IMPORTANCE Infectious disease outbreaks represent a significant problem for public health. Tracing outbreak expansion and understanding the main factors behind emergence and persistence remain critical to effective disease control. Our study allows researchers and public health authorities to use Whole-Genome Sequencing-based methods to trace outbreaks, and shows how available epidemiological information helps to evaluate the factors underpinning outbreak persistence. Taking advantage of all the freely available information placed in public repositories, researchers can accurately establish the expansion of an outbreak beyond original boundaries, and determine the potential risk of a strain to inform health authorities which, in turn, can define target strategies to mitigate expansion and persistence. Finally, we show the need to evaluate strain transmissibility in different geographic contexts to unequivocally associate spread to local or pathogenic factors, an important lesson taken from genomic surveillance of SARS-CoV-2.

TransFlow: a Snakemake workflow for transmission analysis of Mycobacterium tuberculosis whole-genome sequencing data

MOTIVATION

Whole-genome sequencing (WGS) is increasingly used to aid the understanding of Mycobacterium tuberculosis (MTB) transmission. The epidemiological analysis of tuberculosis based on the WGS technique requires a diverse collection of bioinformatics tools. Effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts.

RESULTS

Here, we present TransFlow (Transmission Workflow), a user-friendly, fast, efficient and comprehensive WGS-based transmission analysis pipeline. TransFlow combines some state-of-the-art tools to take transmission analysis from raw sequencing data, through quality control, sequence alignment and variant calling, into downstream transmission clustering, transmission network reconstruction and transmission risk factor inference, together with summary statistics and data visualization in a summary report. TransFlow relies on Snakemake and Conda to resolve dependencies among consecutive processing steps and can be easily adapted to any computation environment.

AVAILABILITY AND IMPLEMENTATION

TransFlow is free available at https://github.com/cvn001/transflow.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Analysis of the twenty-six largest outbreaks of tuberculosis in Aragon using whole-genome sequencing for surveillance purposes

The incidence of tuberculosis in Aragon, Spain, is around ten cases per 100,000 inhabitants. Since 2004, a molecular surveillance protocol has been carried out; therefore, all M. tuberculosis strains are genotyped. Recently, whole-genome sequencing has been implemented for relevant isolates. The aim of this work is to characterise at the molecular level the causative strains of the 26 largest outbreaks of the community (including ten or more cases), genotyped by IS6110-RFLP and causing 26% of tuberculosis cases. To achieve this objective, two or three isolates of each IS6110-cluster belonging to different years were selected for sequencing. We found that strains of lineages L4.8, L4.3 and L4.1.2 were the most frequent. The threshold of 12 SNPs as the maximum distance for confirming the belonging to an outbreak was met for 18 of the 26 IS6110-clusters. Four pairs of isolates with more than 90 SNPs were identified as not belonging to the same strain, and four other pairs were kept in doubt as the number of SNPs was close to 12, between 14 and 35. The study of Regions of Difference revealed that they are lineage conserved. Moreover, we could analyse the IS6110 locations for all genome-sequenced isolates, finding some frequent locations in isolates belonging to the same lineage and certain IS6110 movements between the paired isolates. In the vast majority, these movements were not captured by the IS6110-RFLP pattern. After classifying the genes containing SNP by their functional category, we could confirm that the number of SNPs detected in genes considered as virulence factors and the number of cases the strain produced were not related, suggesting that a particular SNP is more relevant than the number. The characteristics found in the most successful strains in our community could be useful for other researchers in epidemiology, virulence and pathogenesis.

MycoVarP: Mycobacterium Variant and Drug Resistance Prediction Pipeline for Whole-Genome Sequence Data Analysis

Whole-genome sequencing (WGS) provides a comprehensive tool to analyze the bacterial genomes for genotype–phenotype correlations, diversity of single-nucleotide variant (SNV), and their evolution and transmission. Several online pipelines and standalone tools are available for WGS analysis of Mycobacterium tuberculosis (Mtb) complex (MTBC). While they facilitate the processing of WGS data with minimal user expertise, they are either too general, providing little insights into bacterium-specific issues such as gene variations, INDEL/synonymous/PE-PPE (IDP family), and drug resistance from sample data, or are limited to specific objectives, such as drug resistance. It is understood that drug resistance and lineage-specific issues require an elaborate prioritization of identified variants to choose the best target for subsequent therapeutic intervention. Mycobacterium variant pipeline (MycoVarP) addresses these specific issues with a flexible battery of user-defined and default filters. It provides an end-to-end solution for WGS analysis of Mtb variants from the raw reads and performs two quality checks, viz, before trimming and after alignments of reads to the reference genome. MycoVarP maps the annotated variants to the drug-susceptible (DS) database and removes the false-positive variants, provides lineage identification, and predicts potential drug resistance. We have re-analyzed the WGS data reported by Advani et al. (2019) using MycoVarP and identified some additional variants not reported so far. We conclude that MycoVarP will help in identifying nonsynonymous, true-positive, drug resistance–associated variants more effectively and comprehensively, including those within the IDP of the PE-PPE/PGRS family, than possible from the currently available pipelines.

Mutation of Mycobacterium tuberculosis and Implications for Using Whole-Genome Sequencing for Investigating Recent Tuberculosis Transmission

Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis (Mtb) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of WGS results. To estimate the association between infection duration and single nucleotide polymorphism (SNP) accumulation in the Mtb genome, we first analyzed pairwise SNP differences among TB cases from Los Angeles County, California, with strong epidemiologic links. We found that SNP distance alone was insufficient for concluding that cases are linked through recent transmission. Second, we describe a well-characterized cluster of TB cases in California to illustrate the role of genomic data in conclusions regarding recent transmission. Longer presumed latent periods were inconsistently associated with larger SNP differences. Our analyses suggest that WGS alone cannot be used to definitively determine that a case is attributable to recent transmission. Methods for integrating clinical, epidemiologic, and genomic data can guide conclusions regarding the likelihood of recent transmission, providing local public health practitioners with better tools for monitoring and investigating TB transmission.

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis

The Kingman coalescent and its developments are often considered among the most important advances in population genetics of the last decades. Demographic inference based on coalescent theory has been used to reconstruct the population dynamics and evolutionary history of several species, including Mycobacterium tuberculosis (MTB), an important human pathogen causing tuberculosis. One key assumption of the Kingman coalescent is that the number of descendants of different individuals does not vary strongly, and violating this assumption could lead to severe biases caused by model misspecification. Individual lineages of MTB are expected to vary strongly in reproductive success because 1) MTB is potentially under constant selection due to the pressure of the host immune system and of antibiotic treatment, 2) MTB undergoes repeated population bottlenecks when it transmits from one host to the next, and 3) some hosts show much higher transmission rates compared with the average (superspreaders).

Here, we used an approximate Bayesian computation approach to test whether multiple-merger coalescents (MMC), a class of models that allow for large variation in reproductive success among lineages, are more appropriate models to study MTB populations. We considered 11 publicly available whole-genome sequence data sets sampled from local MTB populations and outbreaks and found that MMC had a better fit compared with the Kingman coalescent for 10 of the 11 data sets. These results indicate that the null model for analyzing MTB outbreaks should be reassessed and that past findings based on the Kingman coalescent need to be revisited.

Assessment of closely related Mycobacterium tuberculosis variants with different transmission success and in vitro infection dynamics

Whole genome sequencing (WGS) is able to differentiate closely related Mycobacterium tuberculosis variants within the same transmission cluster. Our aim was to evaluate if this higher discriminatory power may help identify and characterize more actively transmitted variants and understand the factors behind their success. We selected a robust MIRU-VNTR-defined cluster from Almería, Spain (22 cases throughout 2003–2019). WGS allowed discriminating, within the same epidemiological setting, between a successfully transmitted variant and seven closely related variants that did not lead to secondary cases, or were involved in self-limiting transmission (one single secondary case). Intramacrophagic growth of representative variants was evaluated in an in vitro infection model using U937 cells. Intramacrophage multiplication ratios (CFUs at Day 4/CFUs at Day 0) were higher for the actively transmitted variant (range 5.3–10.7) than for the unsuccessfully transmitted closely related variants (1.5–3.95). Two SNPs, mapping at the DNA binding domain of DnaA and at kdpD, were found to be specific of the successful variant.

Whole genome sequencing based differentiation between re-infection and relapse in Indian patients with tuberculosis recurrence, with and without HIV co-infection

INTRODUCTION

Differentiation between relapse and reinfection in cases with tuberculosis (TB) recurrence has important implications for public health, especially in patients with human immunodeficiency virus (HIV) co-infection. We compared Mycobacterial Interspersed Repeat Unit (MIRU) typing and spoligotyping with whole genome sequencing (WGS) to differentiate between relapse and reinfection in patients (HIV-positive and HIV-negative) with TB recurrence. We also assessed the value of WGS to track acquired drug resistance in those with relapse after successful treatment.

METHOD

Forty-one paired M. tuberculosis isolates collected from 20 HIV-positive and 21 HIV-negative patients were subjected to WGS in addition to spoligotyping and MIRU typing. Phylogenetic and Single Nucleotide Substitution (SNP) clustering analyses were performed to determine whether recurrences were due to relapse or re-infection.

RESULTS

Comparison of M. tuberculosis genomes indicated that 95% of TB recurrences in the HIV-negative cohort were due to relapse, while the majority of TB recurrences (75%) in the HIV-positive cohort was due to reinfection (P = 0.0001). New drug resistance mutations were acquired in 5/24 cases (20.8%) that experienced relapse.

CONCLUSIONS

WGS provided increased resolution, but differentiation between relapse and reinfection was broadly consistent with MIRU and spoligotyping. The high contribution of reinfection among HIV infected patients experiencing TB recurrence warrants further study to explore risk factors for TB exposure.

Overlapping prison/community tuberculosis outbreaks in Costa Rica revealed by alternative analysis of suboptimal material

Costa Rica has a low incidence of tuberculosis. Thus, identifying transmission hotspots is key to implement interventions. A tuberculosis outbreak was suspected in a prison in Costa Rica. Given the suboptimal quality of the samples received in our laboratory in Madrid, we applied alternative schemes for their analysis. In the first scheme, we bypassed the standard approach of applying systematic mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) and used a strain-specific polymerase chain reaction (PCR) that allowed identifying a cluster involving six cases (C1). The second scheme followed the canonical MIRU-VNTR path coupled with a whole-genomic amplification step, by which a second unsuspected overlapping cluster (C2), was detected in the same prison. These findings justified the implementation of a surveillance programme adapted to local resources based on a tailored multiplex allele-specific oligonucleotide (ASO)-PCR targeting C1 and C2. Presence of the C2 strain at a different prison was determined. ASO-PCR was applied extensively and alerted to the active circulation of one of the strains within and beyond prisons. Our study shows that alternative methodological strategies may provide useful data in settings with lack of resources for performing systematic standard molecular epidemiology programmes and/or with suboptimal material for analysis.

Genomic Epidemiology Analysis of Infectious Disease Outbreaks Using TransPhylo

Comparing the pathogen genomes from several cases of an infectious disease has the potential to help us understand and control outbreaks. Many methods exist to reconstruct a phylogeny from such genomes, which represents how the genomes are related to one another. However, such a phylogeny is not directly informative about transmission events between individuals. TransPhylo is a software tool implemented as an R package designed to bridge the gap between pathogen phylogenies and transmission trees. TransPhylo is based on a combined model of transmission between hosts and pathogen evolution within each host. It can simulate both phylogenies and transmission trees jointly under this combined model. TransPhylo can also reconstruct a transmission tree based on a dated phylogeny, by exploring the space of transmission trees compatible with the phylogeny. A transmission tree can be represented as a coloring of a phylogeny where each color represents a different host of the pathogen, and TransPhylo provides convenient ways to plot these colorings and explore the results. This article presents the basic protocols that can be used to make the most of TransPhylo. © 2021 The Authors. Basic Protocol 1: First steps with TransPhylo Basic Protocol 2: Simulation of outbreak data Basic Protocol 3: Inference of transmission Basic Protocol 4: Exploring the results of inference.

Towards standardisation: comparison of five whole genome sequencing (WGS) analysis pipelines for detection of epidemiologically linked tuberculosis cases

Background

Whole genome sequencing (WGS) is a reliable tool for studying tuberculosis (TB) transmission. WGS data are usually processed by custom-built analysis pipelines with little standardisation between them.

Aim

To compare the impact of variability of several WGS analysis pipelines used internationally to detect epidemiologically linked TB cases.

Methods

From the Netherlands, 535 Mycobacterium tuberculosis complex (MTBC) strains from 2016 were included. Epidemiological information obtained from municipal health services was available for all mycobacterial interspersed repeat unit-variable number of tandem repeat (MIRU-VNTR) clustered cases. WGS data was analysed using five different pipelines: one core genome multilocus sequence typing (cgMLST) approach and four single nucleotide polymorphism (SNP)-based pipelines developed in Oxford, United Kingdom; Borstel, Germany; Bilthoven, the Netherlands and Copenhagen, Denmark. WGS clusters were defined using a maximum pairwise distance of 12 SNPs/alleles.

Results

The cgMLST approach and Oxford pipeline clustered all epidemiologically linked cases, however, in the other three SNP-based pipelines one epidemiological link was missed due to insufficient coverage. In general, the genetic distances varied between pipelines, reflecting different clustering rates: the cgMLST approach clustered 92 cases, followed by 84, 83, 83 and 82 cases in the SNP-based pipelines from Copenhagen, Oxford, Borstel and Bilthoven respectively.

Conclusion

Concordance in ruling out epidemiological links was high between pipelines, which is an important step in the international validation of WGS data analysis. To increase accuracy in identifying TB transmission clusters, standardisation of crucial WGS criteria and creation of a reference database of representative MTBC sequences would be advisable.

Whole genome sequencing-based analysis of tuberculosis (TB) in migrants: rapid tools for cross-border surveillance and to distinguish between recent transmission in the host country and new importations

Background

The analysis of transmission of tuberculosis (TB) is challenging in areas with a large migrant population. Standard genotyping may fail to differentiate transmission within the host country from new importations, which is key from an epidemiological perspective.

Aim

To propose a new strategy to simplify and optimise cross-border surveillance of tuberculosis and to distinguish between recent transmission in the host country and new importations

Methods

We selected 10 clusters, defined by 24-locus mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR), from a population in Spain rich in migrants from eastern Europe, north Africa and west Africa and reanalysed 66 isolates by whole-genome sequencing (WGS). A multiplex-allele-specific PCR was designed to target strain-specific marker single nucleotide polymorphisms (SNPs), identified from WGS data, to optimise the surveillance of the most complex cluster.

Results

In five of 10 clusters not all isolates showed the short genetic distances expected for recent transmission and revealed a higher number of SNPs, thus suggesting independent importations of prevalent strains in the country of origin. In the most complex cluster, rich in Moroccan cases, a multiplex allele-specific oligonucleotide-PCR (ASO-PCR) targeting the marker SNPs for the transmission subcluster enabled us to prospectively identify new secondary cases. The ASO-PCR-based strategy was transferred and applied in Morocco, demonstrating that the strain was prevalent in the country.

Conclusion

We provide a new model for optimising the analysis of cross-border surveillance of TB transmission in the scenario of global migration.

Mycobacterium tuberculosis clinical isolates carry mutational signatures of host immune environments

Mycobacterium tuberculosis (Mtb) infection results in a spectrum of clinical and histopathologic manifestations. It has been proposed that the environmental and immune pressures associated with different contexts of infection have different consequences for the associated bacterial populations, affecting drug susceptibility and the emergence of resistance. However, there is little concrete evidence for this model. We prospectively collected sputum samples from 18 newly diagnosed and treatment-naïve patients with tuberculosis and sequenced 795 colony-derived Mtb isolates. Mutant accumulation rates varied considerably between different bacilli isolated from the same individual, and where high rates of mutation were observed, the mutational spectrum was consistent with reactive oxygen species-induced mutagenesis. Elevated bacterial mutation rates were identified in isolates from HIV-negative but not HIV-positive individuals, suggesting that they were immune-driven. These results support the model that mutagenesis of Mtb in vivo is modulated by the host environment, which could drive the emergence of variants associated with drug resistance in a host-dependent manner.

Tools to implement the World Health Organization End TB Strategy: Addressing common challenges in high and low endemic countries

AIM

The purpose of this viewpoint is to summarize the advantages and constraints of the tools and strategies available for reducing the annual incidence of tuberculosis (TB) by implementing the World Health Organization (WHO) End TB Strategy and the linked WHO TB Elimination Framework, with special reference to Oman.

METHODS

The case-study was built based on the presentations and discussions at an international workshop on TB elimination in low incidence countries organized by the Ministry of Health, Oman, which took place from September 5 to September 7, 2019, and supported by the WHO and European Society of Clinical Microbiology and Infectious Diseases (ESCMID).

RESULTS

Existing tools were reviewed, including the screening of migrants for latent TB infection (LTBI) with interferon-gamma release assays, clinical examination for active pulmonary TB (APTB) including chest X-rays, organization of laboratory services, and the existing centres for mandatory health examination of pre-arrival or arriving migrants, including examination for APTB. The need for public-private partnerships to handle the burden of screening arriving migrants for active TB was discussed at length and different models for financing were reviewed.

CONCLUSIONS

In a country with a high proportion of migrants from high endemic countries, screening for LTBI is of high priority. Molecular typing and the development of public-private partnerships are needed.

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.

High-resolution mapping of tuberculosis transmission: Whole genome sequencing and phylogenetic modelling of a cohort from Valencia Region, Spain

BACKGROUND

Whole genome sequencing provides better delineation of transmission clusters in Mycobacterium tuberculosis than traditional methods. However, its ability to reveal individual transmission links within clusters is limited. Here, we used a 2-step approach based on Bayesian transmission reconstruction to (1) identify likely index and missing cases, (2) determine risk factors associated with transmitters, and (3) estimate when transmission happened.

METHODS AND FINDINGS

We developed our transmission reconstruction method using genomic and epidemiological data from a population-based study from Valencia Region, Spain. Tuberculosis (TB) incidence during the study period was 8.4 cases per 100,000 people. While the study is ongoing, the sampling frame for this work includes notified TB cases between 1 January 2014 and 31 December 2016. We identified a total of 21 transmission clusters that fulfilled the criteria for analysis. These contained a total of 117 individuals diagnosed with active TB (109 with epidemiological data). Demographic characteristics of the study population were as follows: 80/109 (73%) individuals were Spanish-born, 76/109 (70%) individuals were men, and the mean age was 42.51 years (SD 18.46). We found that 66/109 (61%) TB patients were sputum positive at diagnosis, and 10/109 (9%) were HIV positive. We used the data to reveal individual transmission links, and to identify index cases, missing cases, likely transmitters, and associated transmission risk factors. Our Bayesian inference approach suggests that at least 60% of index cases are likely misidentified by local public health. Our data also suggest that factors associated with likely transmitters are different to those of simply being in a transmission cluster, highlighting the importance of differentiating between these 2 phenomena. Our data suggest that type 2 diabetes mellitus is a risk factor associated with being a transmitter (odds ratio 0.19 [95% CI 0.02-1.10], p < 0.003). Finally, we used the most likely timing for transmission events to study when TB transmission occurred; we identified that 5/14 (35.7%) cases likely transmitted TB well before symptom onset, and these were largely sputum negative at diagnosis. Limited within-cluster diversity does not allow us to extrapolate our findings to the whole TB population in Valencia Region.

CONCLUSIONS

In this study, we found that index cases are often misidentified, with downstream consequences for epidemiological investigations because likely transmitters can be missed. Our findings regarding inferred transmission timing suggest that TB transmission can occur before patient symptom onset, suggesting also that TB transmits during sub-clinical disease. This result has direct implications for diagnosing TB and reducing transmission. Overall, we show that a transition to individual-based genomic epidemiology will likely close some of the knowledge gaps in TB transmission and may redirect efforts towards cost-effective contact investigations for improved TB control.

The molecular clock of Mycobacterium tuberculosis

The molecular clock and its phylogenetic applications to genomic data have changed how we study and understand one of the major human pathogens, Mycobacterium tuberculosis (MTB), the etiologic agent of tuberculosis. Genome sequences of MTB strains sampled at different times are increasingly used to infer when a particular outbreak begun, when a drug-resistant clone appeared and expanded, or when a strain was introduced into a specific region. Despite the growing importance of the molecular clock in tuberculosis research, there is a lack of consensus as to whether MTB displays a clocklike behavior and about its rate of evolution. Here we performed a systematic study of the molecular clock of MTB on a large genomic data set (6,285 strains), covering different epidemiological settings and most of the known global diversity. We found that sampling times below 15-20 years were often insufficient to calibrate the clock of MTB. For data sets where such calibration was possible, we obtained a clock rate between 1x10-8 and 5x10-7 nucleotide changes per-site-per-year (0.04-2.2 SNPs per-genome-per-year), with substantial differences between clades. These estimates were not strongly dependent on the time of the calibration points as they changed only marginally when we used epidemiological isolates (sampled in the last 40 years) or three ancient DNA samples (about 1,000 years old) to calibrate the tree. Additionally, the uncertainty and the discrepancies in the results of different methods were sometimes large, highlighting the importance of using different methods, and of considering carefully their assumptions and limitations.

A Mycobacterium tuberculosis Beijing strain persists at high rates and extends its geographic boundaries 20 years after importation

Transmission of Beijing Mycobacterium tuberculosis can be investigated based on genotypic analysis of clinical isolates. A Beijing strain began to spread on Gran Canaria Island, Spain, at the end of the last century. In 1996, only 3 years after its importation to the island, its frequency had increased to 27.1% of all the isolates. The strain was tracked during the following years, and the most recent data obtained corresponded to 2007-8, when its presence continued to be alarming (21%). In the current study, we updated data on the distribution of this strain 20 years (2013–2014) after it was first detected on the island and extended the analysis for the first time to all the mycobacteriology laboratories covering the population of the Canary Island archipelago. Rapid updating was enabled by means of 2 different strain-specific PCRs: one targeting a peculiar feature of the strain, which was identified based on an IS6110 copy mapping in the Rv2180c gene, and a newly defined strain-specific single nucleotide polymorphism, which was identified by whole-genome sequencing. The results showed that the strain has remained highly prevalent (20.90% of all isolates), has spread throughout the neighbouring islands, and has also reached high representativeness in them (11–32%).

Complete Genome Sequence of Mycobacterium tuberculosis DKC2, the Predominant Danish Outbreak Strain

The largest clonal outbreak of Mycobacterium tuberculosis infection in Scandinavia has been monitored by the International Reference Laboratory of Mycobacteriology (IRLM) since 1992. Here, we present the complete genome sequence of M. tuberculosis strain DKC2 substrain PP1, a representative isolate collected in 1993 from a Danish patient with pulmonary tuberculosis.

The largest clonal outbreak of Mycobacterium tuberculosis infection in Scandinavia has been monitored by the International Reference Laboratory of Mycobacteriology (IRLM) since 1992. Here, we present the complete genome sequence of M. tuberculosis strain DKC2 substrain PP1, a representative isolate collected in 1993 from a Danish patient with pulmonary tuberculosis.

A Major Mycobacterium tuberculosis outbreak caused by one specific genotype in a low-incidence country: Exploring gene profile virulence explanations

Denmark, a tuberculosis low burden country, still experiences significant active Mycobacterium tuberculosis (Mtb) transmission, especially with one specific genotype named Cluster 2/1112-15 (C2), the most prevalent lineage in Scandinavia. In addition to environmental factors, antibiotic resistance, and human genetics, there is increasing evidence that Mtb strain variation plays a role for the outcome of infection and disease. In this study, we explore the reasons for the success of the C2 genotype by analysing strain specific polymorphisms identified through whole genome sequencing of all C2 isolates identified in Denmark between 1992 and 2014 (n = 952), and the demographic distribution of C2. Of 234 non-synonymous (NS) monomorphic SNPs found in C2 in comparison with Mtb reference strain H37Rv, 23 were in genes previously reported to be involved in Mtb virulence. Of these 23 SNPs, three were specific for C2 including a NS mutation in a gene associated with hyper-virulence. We show that the genotype is readily transmitted to different ethnicities and is also found outside Denmark. Our data suggest that strain specific virulence factor variations are important for the success of the C2 genotype. These factors, likely in combination with poor TB control, seem to be the main drivers of C2 success.

MIRU-profiler: a rapid tool for determination of 24-loci MIRU-VNTR profiles from assembled genomes of Mycobacterium tuberculosis

Background

Tuberculosis (TB) resulted in an estimated 1.7 million deaths in the year 2016. The disease is caused by the members of Mycobacterium tuberculosis complex, which includes Mycobacterium tuberculosis, Mycobacterium bovis and other closely related TB causing organisms. In order to understand the epidemiological dynamics of TB, national TB control programs often conduct standardized genotyping at 24 Mycobacterial-Interspersed-Repetitive-Units (MIRU)-Variable-Number-of-Tandem-Repeats (VNTR) loci. With the advent of next generation sequencing technology, whole-genome sequencing (WGS) has been widely used for studying TB transmission. However, an open-source software that can connect WGS and MIRU-VNTR typing is currently unavailable, which hinders interlaboratory communication. In this manuscript, we introduce the MIRU-profiler program which could be used for prediction of MIRU-VNTR profile from WGS of M. tuberculosis.

Implementation

The MIRU-profiler is implemented in shell scripting language and depends on EMBOSS software. The in-silico workflow of MIRU-profiler is similar to those described in the laboratory manuals for genotyping M. tuberculosis. Given an input genome sequence, the MIRU-profiler computes alleles at the standard 24-loci based on in-silico PCR amplicon lengths. The final output is a tab-delimited text file detailing the 24-loci MIRU-VNTR pattern of the input sequence.

Validation

The MIRU-profiler was validated on four datasets: complete genomes from NCBI-GenBank (n = 11), complete genomes for locally isolated strains sequenced using PacBio (n = 4), complete genomes for BCG vaccine strains (n = 2) and draft genomes based on 250 bp paired-end Illumina reads (n = 106).

Results

The digital MIRU-VNTR results were identical to the experimental genotyping results for complete genomes of locally isolated strains, BCG vaccine strains and five out of 11 genomes from the NCBI-GenBank. For draft genomes based on short Illumina reads, 21 out of 24 loci were inferred with a high accuracy, while a number of inaccuracies were recorded for three specific loci (ETRA, QUB11b and QUB26). One of the unique features of the MIRU-profiler was its ability to process multiple genomes in a batch. This feature was tested on all complete M. tuberculosis genome (n = 157), for which results were successfully obtained in approximately 14 min.

Conclusion

The MIRU-profiler is a rapid tool for inference of digital MIRU-VNTR profile from the assembled genome sequences. The tool can accurately infer repeat numbers at the standard 24 or 21/24 MIRU-VNTR loci from the complete or draft genomes respectively. Thus, the tool is expected to bridge the communication gap between the laboratories using WGS and those using the conventional MIRU-VNTR typing.