Inferring patient to patient transmission of Mycobacterium tuberculosis from whole genome sequencing data

Drug resistance and epidemiological success of modern Mycobacterium tuberculosis lineages in western India

BACKGROUND

Transmission is contributing to the slow decline of tuberculosis (TB) incidence globally. Drivers of TB transmission in India, the country estimated to carry a quarter of the World's burden, are not well studied. We conducted a genomic epidemiology study to compare epidemiological success, host factors and drug resistance (DR) among the four major Mycobacterium tuberculosis (Mtb) lineages (L1-4) circulating in Pune, India.

METHODS

We performed whole-genome sequencing (WGS) of Mtb sputum culture-positive isolates from participants in two prospective cohort studies and predicted genotypic susceptibility using a validated random forest model. We used maximum likelihood estimation to build phylogenies. We compared lineage specific phylogenetic and time-scaled metrics to assess epidemiological success.

RESULTS

Of the 642 isolates that underwent WGS, 612 met sequence quality criteria. Most isolates belonged to L3 (44.6%). The majority (61.1%) of multidrug-resistant isolates belonged to L2 (P < 0.001). In molecular dating, L2 demonstrated a higher rate and more recent resistance acquisition. We measured higher clustering, and time-scaled haplotypic density (THD) for L4 and L2 compared to L3 and/or L1 suggesting higher epidemiological success. L4 demonstrated higher THD and clustering (OR 5.1 (95% CI 2.3-12.3) in multivariate models controlling for host factors and DR.

CONCLUSION

L2 shows a higher frequency of DR and both L2 and L4 demonstrate evidence of higher epidemiological success than L3 or L1 in the study setting. Our findings highlight the need for contact tracing around TB cases, and heightened surveillance of TB DR in India.

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.

Whole-Genome sequencing in routine Mycobacterium bovis epidemiology - scoping the potential

Mycobacterium bovis the main agent of bovine tuberculosis (bTB), presents as a series of spatially-localised micro-epidemics across landscapes. Classical molecular typing methods applied to these micro-epidemics, based on genotyping a few variable loci, have significantly improved our understanding of potential epidemiological links between outbreaks. However, they have limited utility owing to low resolution. Conversely, whole-genome sequencing (WGS) provides the highest resolution data available for molecular epidemiology, producing richer outbreak tracing, insights into phylogeography and epidemic evolutionary history. We illustrate these advantages by focusing on a common single lineage of M. bovis (1.140) from Northern Ireland. Specifically, we investigate the spatial sub-structure of 20 years of herd-level multi locus VNTR analysis (MLVA) surveillance data and WGS data from a down sampled subset of isolates of this MLVA type over the same time frame. We mapped 2108 isolate locations of MLVA type 1.140 over the years 2000-2022. We also mapped the locations of 148 contemporary WGS isolates from this lineage, over a similar geographic range, stratifying by single nucleotide polymorphism (SNP) relatedness cut-offs of 15 SNPs. We determined a putative core range for the 1.140 MLVA type and SNP-defined sequence clusters using a 50 % kernel density estimate, using cattle movement data to inform on likely sources of WGS isolates found outside of core ranges. Finally, we applied Bayesian phylogenetic methods to investigate past population history and reproductive number of the 1.140 M. bovis lineage. We demonstrate that WGS SNP-defined clusters exhibit smaller core ranges than the established MLVA type - facilitating superior disease tracing. We also demonstrate the superior functionality of WGS data in determining how this lineage was disseminated across the landscape, likely via cattle movement and to infer how its effective population size and reproductive number has been in flux since its emergence. These initial findings highlight the potential of WGS data for routine monitoring of bTB outbreaks.

The paradoxes of Mycobacterium tuberculosis molecular evolution and consequences for the inference of tuberculosis emergence date

The date of Mycobacterium tuberculosis complex emergence has been the subject of long debates. New studies joining archaeological efforts with sequencing methods raise high hopes for solving whether this emergence is closer to 70,000 or to 6000 years before present. Inferring the date of emergence of this pathogen based on sequence data requires a molecular clock. Several clocks inferred from different types of loci and/or different samples, using both sound reasoning and reliable data, are actually very different, which we refer to as the paradoxes of M. tuberculosis molecular evolution. After having presented these paradoxes, we will remind the limits of the molecular clocks used in the different studies such as the assumption of homogeneous substitution rate. We will then review recent results that shed new light on the characteristics of M. tuberculosis molecular evolution: traces of diverse selection pressures, the impact of host dynamics, etc. We provide some ideas on what to do next to get nearer to a reliable dating of Mycobacterium tuberculosis complex emergence. Among them, the collection of additional remains from ancient tuberculosis seems still essential.

Clinical Whole-Genome Sequencing Assay for Rapid Mycobacterium tuberculosis Complex First-Line Drug Susceptibility Testing and Phylogenetic Relatedness Analysis

The global rise of drug resistant tuberculosis has highlighted the need for improved diagnostic technologies that provide rapid and reliable drug resistance results. Here, we develop and validate a whole genome sequencing (WGS)-based test for identification of mycobacterium tuberculosis complex (MTB) drug resistance to rifampin, isoniazid, pyrazinamide, ethambutol, and streptomycin. Through comparative analysis of drug resistance results from WGS-based testing and phenotypic drug susceptibility testing (DST) of 38 clinical MTB isolates from patients receiving care in Los Angeles, CA, we found an overall concordance between methods of 97.4% with equivalent performance across culture media. Critically, prospective analysis of 11 isolates showed that WGS-based testing provides results an average of 36 days faster than phenotypic culture-based methods. We showcase the additional benefits of WGS data by investigating a suspected laboratory contamination event and using phylogenetic analysis to search for cryptic local transmission, finding no evidence of community spread amongst our patient population in the past six years. WGS-based testing for MTB drug resistance has the potential to greatly improve diagnosis of drug resistant MTB by accelerating turnaround time while maintaining accuracy and providing additional benefits for infection control, lab safety, and public health applications.

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

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

Investigating in vivo Mycobacterium avium subsp. paratuberculosis microevolution and mixed strain infections

Mycobacterium avium subsp. paratuberculosis (MAP) causes Johne's Disease (JD) in ruminants, which is responsible for significant economic loss to the global dairy industry. Mixed strain infection (MSI) refers to the concurrent infection of a susceptible host with genetically distinct strains of a pathogen, whereas within-host changes in an infecting strain leading to genetically distinguishable progeny is called microevolution. The two processes can influence host-pathogen dynamics, disease progression and outcomes, but not much is known about their prevalence and impact on JD. Therefore, we obtained up to 10 MAP isolates each from 14 high-shedding animals and subjected them to whole-genome sequencing. Twelve of the 14 animals examined showed evidence for the presence of MSIs and microevolution, while the genotypes of MAP isolates from the remaining two animals could be attributed solely to microevolution. All MAP isolates that were otherwise isogenic had differences in short sequence repeats (SSRs), of which SSR1 and SSR2 were the most diverse and homoplastic. Variations in SSR1 and SSR2, which are located in ORF1 and ORF2, respectively, affect the genetic reading frame, leading to protein products with altered sequences and computed structures. The ORF1 gene product is predicted to be a MAP surface protein with possible roles in host immune modulation, but nothing could be inferred regarding the function of ORF2. Both genes are conserved in Mycobacterium avium complex members, but SSR1-based modulation of ORF1 reading frames seems to only occur in MAP, which could have potential implications on the infectivity of this pathogen. IMPORTANCE Johne's disease (JD) is a major problem in dairy animals, and concerns have been raised regarding the association of Mycobacterium avium subsp. paratuberculosis (MAP) with Crohn's disease in humans. MAP is an extremely slow-growing bacterium with low genome evolutionary rates. Certain short sequence repeats (SSR1 and SSR2) in the MAP chromosome are highly variable and evolve at a faster rate than the rest of the chromosome. In the current study, multiple MAP isolates with genetic variations such as single-nucleotide polymorphisms, and more noticeably, diverse SSRs, could simultaneously infect animals. Variations in SSR1 and SSR2 affect the products of the respective genes containing them. Since multiple MAP isolates can infect the same animal and the possibility that the pathogen undergoes further changes within the host due to unstable SSRs, this could provide a compensative mechanism for an otherwise slow-evolving pathogen to increase phenotypic diversity for overcoming host responses.

GraphSNP: an interactive distance viewer for investigating outbreaks and transmission networks using a graph approach

BACKGROUND

Cluster and transmission analysis utilising pairwise SNP distance are increasingly used in genomic epidemiological studies. However, current methods are often challenging to install and use, and lack interactive functionalities for easy data exploration.

RESULTS

GraphSNP is an interactive visualisation tool running in a web browser that allows users to rapidly generate pairwise SNP distance networks, investigate SNP distance distributions, identify clusters of related organisms, and reconstruct transmission routes. The functionality of GraphSNP is demonstrated using examples from recent multi-drug resistant bacterial outbreaks in healthcare settings.

CONCLUSIONS

GraphSNP is freely available at https://github.com/nalarbp/graphsnp . An online version of GraphSNP, including demonstration datasets, input templates, and quick start guide is available for use at https://graphsnp.fordelab.com .

Distribution and origins of Mycobacterium tuberculosis L4 in Southeast Asia

Molecular and genomic studies have revealed that Mycobacterium tuberculosis Lineage 4 (L4, Euro-American lineage) emerged in Europe before becoming distributed around the globe by trade routes, colonial migration and other historical connections. Although L4 accounts for tens or hundreds of thousands of tuberculosis (TB) cases in multiple Southeast Asian countries, phylogeographical studies have either focused on a single country or just included Southeast Asia as part of a global analysis. Therefore, we interrogated public genomic data to investigate the historical patterns underlying the distribution of L4 in Southeast Asia and surrounding countries. We downloaded 6037 genomes associated with 29 published studies, focusing on global analyses of L4 and Asian studies of M. tuberculosis. We identified 2256 L4 genomes including 968 from Asia. We show that 81 % of L4 in Thailand, 51 % of L4 in Vietnam and 9 % of L4 in Indonesia belong to sub-lineages of L4 that are rarely seen outside East and Southeast Asia (L4.2.2, L4.4.2 and L4.5). These sub-lineages have spread between East and Southeast Asian countries, with no recent European ancestor. Although there is considerable uncertainty about the exact direction and order of intra-Asian M. tuberculosis dispersal, due to differing sampling frames between countries, our analysis suggests that China may be the intermediate location between Europe and Southeast Asia for two of the three predominantly East and Southeast Asian L4 sub-lineages (L4.2.2 and L4.5). This new perspective on L4 in Southeast Asia raises the possibility of investigating host population-specific evolution and highlights the need for more structured sampling from Southeast Asian countries to provide more certainty of the historical and current routes of dispersal.

Whole-genome sequencing of presumptive MDR-TB isolates from a tertiary healthcare setting in Mumbai

OBJECTIVES

Whole-genome sequencing (WGS) of Mycobacterium tuberculosis (MTB), proven to be a better alternative when compared with the combined sensitivity and specificity of all other modalities for diagnosis of tuberculosis (TB), aids epidemiological surveillance investigations by combining the current research with diagnostics. This study was conducted to identify and resolve operational challenges in performing WGS-based drug resistance testing (DRT) for MTB in a TB culture and drug susceptibility testing (DST) laboratory. Three critical, non-redundant steps for WGS-based DRT were tested: viz. DNA extraction, high-throughput paired-end next-generation sequencing (NGS), and genomic analysis pipeline for automated reporting of WGS-based DRT.

METHODS

DNA was extracted from 100 liquid culture isolates on a mycobacterial growth indicator tube (MGIT) using DNEASY Ultraclean Microbial Kit (Qiagen, USA) as per the manufacturer's instructions. Illumina paired-end sequencing was performed. All analysis steps were automated using custom python scripts, requiring no intervention. Variant calling was performed as per the World Health Organization (WHO) technical guide.

RESULTS

The number of cultures resistant to rifampicin, isoniazid, pyrazinamide, ethambutol, and streptomycin was 89, 88, 35, 67, and 73, respectively. Resistance to amikacin, kanamycin, and capreomycin was found in 15, 17, and 15 cultures, respectively. Seventy cultures were resistant to fluoroquinolones, four were resistant to ethionamide, and 12 were resistant to linezolid. Six cultures were resistant to only one of the 18 drugs tested. Seventy-five cultures were resistant to more than three anti-TB drugs. One culture was resistant to 13 of the 18 anti-TB drugs tested for this study. The maximum number of variants were observed in the rpoB gene (n = 93, 93%), wherein the Ser450Leu was the predominant mutation (n = 68, 73%). Ser315Thr was the most common variant (n = 86, 97%) that encoded resistance to isoniazid. The Lys43Arg variant encodes resistance to streptomycin and was the third most predominant variant (n = 65, 89%). In addition to the high levels of resistance observed in the dataset, we also observed a high proportion of Beijing strains (n = 63, 63%).

CONCLUSION

Compared with results from routine diagnostics based on the 'Guidelines on Programmatic Management of Drug-Resistant TB (PMDT) in India', none of the samples had DST available for all 18 drugs. This represents a gap in PMDT guidelines. The WGS-DRT must be considered as the primary DST method after a sample is flagged rifampicin-resistant by cartridge-based nucleic acid amplification testing (CBNAAT). With several research studies currently underway globally to identify novel variants associated with drug resistance and classifiy their minimum inhibitory coefficients, WGS-DRT presents a scalable technology that updates analytical pipelines, relegating the need for changing microbiological protocols.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Whole-Genome Sequencing and Epidemiological Investigation of Tuberculosis Outbreaks in High Schools in Hunan, China

Background

Tuberculosis (TB) seriously threatens individual and public health. Recently, TB outbreaks in schools have been reported more frequently in China and have attracted widespread attention. We reported three TB outbreaks in high schools in Hunan Province, China.

Methods

When a tuberculosis patient was reported in a school, we carried out field epidemiological investigations, including tuberculin skin testing (TST), chest X-ray (CXR) and laboratory test for all close contacts, and whole-genome sequencing (WGS) analyses to understand the transmission patterns, the causes and the risk factors for the outbreaks, thereby providing a foundation for the control of TB epidemics in schools.

Results

A total of 49 students with TB patients were identified in the three schools where TB outbreaks occurred, including nine patients in School A, 14 patients in School B, and 26 patients in School C. In Schools A, B and C, the putative attack rates in the classes of the index case were 13.8% (8/58), 7.6% (5/66), and 40.4% (21/52), while the putative attack rates of expanding screening in the school were 0.3% (1/361), 0.2% (9/3955), and 0.2% (5/2080), respectively. Thirteen patients had patient delay, with a median delay interval of 69 days (IQR 30.5–113 days). Twelve patients had a healthcare diagnostic delay with a median delay interval of 32 days (IQR 24–82 days). Phylogenetic analysis of culture-positive patients revealed that most of them shared a small genetic distance (≤12 SNPs), with three separate genetic clusters (including one MDR-TB genomic cluster), indicating the recent transmission of Mycobacterium tuberculosis strains.

Conclusion

This combination of field investigation and WGS analysis revealed the transmission of three TB outbreaks in schools. Reinforced implementation is needed to improve timely case finding and reduce diagnosis delay in routine TB control in the school population.

A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis

Long diagnostic wait times hinder international efforts to address antibiotic resistance in M. tuberculosis. Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution. However, generalizability and clinical adoption have been limited by a lack of interpretability, especially in deep learning methods. Here, we present two deep convolutional neural networks that predict antibiotic resistance phenotypes of M. tuberculosis isolates: a multi-drug CNN (MD-CNN), that predicts resistance to 13 antibiotics based on 18 genomic loci, with AUCs 82.6-99.5% and higher sensitivity than state-of-the-art methods; and a set of 13 single-drug CNNs (SD-CNN) with AUCs 80.1-97.1% and higher specificity than the previous state-of-the-art. Using saliency methods to evaluate the contribution of input sequence features to the SD-CNN predictions, we identify 18 sites in the genome not previously associated with resistance. The CNN models permit functional variant discovery, biologically meaningful interpretation, and clinical applicability.

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.

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.

Tuberculosis Outbreak in an Educational Institution in Henan Province, China

On June 17, 2018, a case of pulmonary tuberculosis (TB) was reported among students at a senior high school in Luoning, China. The outbreak encompassed a total of 23 cases along with TB screening in the whole school by means of PPD and chest X-ray. By the end of September 2018, the entire 9 cases cultured positive had epidemiological association. All of the 9 Mycobacterium tuberculosis (Mtb) isolates available were sensitive to all drugs tested and had similar spoligotyping and 15 loci mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) profile. Whole-genome sequencing (WGS) of the Mtb isolates revealed 20 variable nucleotide positions within 8 cases, indicating a clonal outbreak. The index case, which was first identified and diagnosed, is separated from the cluster by a minimum number of 95 distinct SNPs. Minimum distance spanning tree (MST) indicted that the 8 cases were indeed part of a single transmission chain. It was concluded that this is an epidemic situation of TB outbreak exposed by the aggrieved index case at school, which was caused by the veiled infectious case wherein a student was suffering from TB and attending school simultaneously.

Population structure, biogeography and transmissibility of Mycobacterium tuberculosis

Mycobacterium tuberculosis is a clonal pathogen proposed to have co-evolved with its human host for millennia, yet our understanding of its genomic diversity and biogeography remains incomplete. Here we use a combination of phylogenetics and dimensionality reduction to reevaluate the population structure of M. tuberculosis, providing an in-depth analysis of the ancient Indo-Oceanic Lineage 1 and the modern Central Asian Lineage 3, and expanding our understanding of Lineages 2 and 4. We assess sub-lineages using genomic sequences from 4939 pan-susceptible strains, and find 30 new genetically distinct clades that we validate in a dataset of 4645 independent isolates. We find a consistent geographically restricted or unrestricted pattern for 20 groups, including three groups of Lineage 1. The distribution of terminal branch lengths across the M. tuberculosis phylogeny supports the hypothesis of a higher transmissibility of Lineages 2 and 4, in comparison with Lineages 3 and 1, on a global scale. We define an expanded barcode of 95 single nucleotide substitutions that allows rapid identification of 69 M. tuberculosis sub-lineages and 26 additional internal groups. Our results paint a higher resolution picture of the M. tuberculosis phylogeny and biogeography.

The Relevance of Genomic Epidemiology for Control of Tuberculosis in West Africa

Tuberculosis (TB), an airborne infectious disease caused by Mycobacterium tuberculosis complex (MTBC), remains a global health problem. West Africa has a unique epidemiology of TB that is characterized by medium- to high-prevalence. Moreover, the geographical restriction of M. africanum to the sub-region makes West Africa have an extra burden to deal with a two-in-one pathogen. The region is also burdened with low case detection, late reporting, poor treatment adherence leading to development of drug resistance and relapse. Sporadic studies conducted within the subregion report higher burden of drug resistant TB (DRTB) than previously thought. The need for more sensitive and robust tools for routine surveillance as well as to understand the mechanisms of DRTB and transmission dynamics for the design of effective control tools, cannot be overemphasized. The advancement in molecular biology tools including traditional fingerprinting and next generation sequencing (NGS) technologies offer reliable tools for genomic epidemiology. Genomic epidemiology provides in-depth insight of the nature of pathogens, circulating strains and their spread as well as prompt detection of the emergence of new strains. It also offers the opportunity to monitor treatment and evaluate interventions. Furthermore, genomic epidemiology can be used to understand potential emergence and spread of drug resistant strains and resistance mechanisms allowing the design of simple but rapid tools. In this review, we will describe the local epidemiology of MTBC, highlight past and current investigations toward understanding their biology and spread as well as discuss the relevance of genomic epidemiology studies to TB control in West Africa.

Social network analysis and whole-genome sequencing to evaluate disease transmission in a large, dynamic population: A study of avian mycobacteriosis in zoo birds

This study combined a social network analysis and whole-genome sequencing (WGS) to test for general patterns of contagious spread of a mycobacterial infection for which pathways of disease acquisition are not well understood. Our population included 275 cases diagnosed with avian mycobacteriosis that were nested in a source population of 16,430 birds at San Diego Zoo Wildlife Alliance facilities from 1992 through mid-2014. Mycobacteria species were determined using conventional methods and whole genome sequencing (WGS). Mycobacterium avium avium (MAA) and Mycobacterium genavense were the most common species of mycobacteria identified and were present in different proportions across bird taxa. A social network for the birds was constructed from the source population to identify directly and indirectly connected cases during time periods relevant to disease transmission. Associations between network connectivity and genetic similarity of mycobacteria (as determined by clusters of genotypes separated by few single nucleotide polymorphisms, or SNPs) were then evaluated in observed and randomly generated network permutations. Findings showed that some genotypes clustered along pathways of bird connectivity, while others were dispersed throughout the network. The proportion of directly connected birds having a similar mycobacterial genotype was 0.36 and significant (p<0.05). This proportion was higher (0.58) and significant for MAA but not for M. genavense. Evaluations of SNP distributions also showed genotypes of MAA were more related in connected birds than expected by chance; however, no significant patterns of genetic relatedness were identified for M. genavense, although data were sparse. Integrating the WGS analysis of mycobacteria with a social network analysis of their host birds revealed significant genetic clustering along pathways of connectivity, namely for MAA. These findings are consistent with a contagious process occurring in some, but not all, case clusters.

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.

A population-based genomic epidemiological study of the source of tuberculosis infections in an emerging city: Shenzhen, China

Background

Tuberculosis (TB) in emerging cities is often a disease of recent immigrants, and understanding this epidemiology is crucial for designing effective control and prevention strategies.

Methods

We conducted a retrospective population-based genomic epidemiological study of culture-positive pulmonary TB patients diagnosed between June 2014 and November 2017 in the Bao'an District of Shenzhen, a Chinese city with dramatic recent growth. After whole genome sequencing, transmission clusters were defined as strains differing by no more than 12 SNPs.

Findings

Of 1696 culture-positive TB patients, 93•8% (1591/1696) were migrants, with 51•6% (821/1591) employed in housekeeping or unemployed. Of the 1460 migrants with known residence time, 47•7% (697/1460) developed TB within two years after arriving in Bao'an. Only 12•2% (207/1696) of Bao'an isolates were in genomic clusters, indicating that recent transmission was not the primary cause of TB in Bao'an. The isolates’ median terminal branch length was 56 SNPs, more than could have accumulated since the arrival of the migrants in Bao'an. The migrants’ isolates had genotypic distributions similar to those in their home provinces. One strain isolated in Bao'an belonged to a clade circulating in the patient's home province, providing further evidence that the strains were brought to Bao'an with the migrants.

Interpretation

TB in the Bao'an District is principally caused by reactivation of infections acquired by migrants in their home provinces. Nearly half developed TB within two years after arriving in Bao'an, suggesting a need for increased TB screening of migrants, especially housekeeping workers and the unemployed.

Funding

Sanming Project of Medicine in Shenzhen; National Science and Technology Major Project of China; Natural Science Foundation of China.

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.

Mycobacterium tuberculosis complex in wildlife: Review of current applications of antemortem and postmortem diagnosis

Tuberculosis (TB) is a chronic inflammatory and zoonotic disease caused by Mycobacterium tuberculosis complex (MTBC) members, which affects various domestic animals, wildlife, and humans. Some wild animals serve as reservoir hosts in the transmission and epidemiology of the disease. Therefore, the monitoring and surveillance of both wild and domestic hosts are critical for prevention and control strategies. For TB diagnosis, the single intradermal tuberculin test or the single comparative intradermal tuberculin test, and the gamma-interferon test, which is regarded as an ancillary test, are used. Postmortem examination can identify granulomatous lesions compatible with a diagnosis of TB. In contrast, smears of the lesions can be stained for acid-fast bacilli, and samples of the affected organs can be subjected to histopathological analyses. Culture is the gold standard test for isolating mycobacterial bacilli because it has high sensitivity and specificity compared with other methods. Serology for antibody detection allows the testing of many samples simply, rapidly, and inexpensively, and the protocol can be standardized in different laboratories. Molecular biological analyses are also applicable to trace the epidemiology of the disease. In conclusion, reviewing the various techniques used in MTBC diagnosis can help establish guidelines for researchers when choosing a particular diagnostic method depending on the situation at hand, be it disease outbreaks in wildlife or for epidemiological studies. This is because a good understanding of various diagnostic techniques will aid in monitoring and managing emerging pandemic threats of infectious diseases from wildlife and also preventing the potential spread of zoonotic TB to livestock and humans. This review aimed to provide up-to-date information on different techniques used for diagnosing TB at the interfaces between wildlife, livestock, and humans.

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.

Genomic variant-identification methods may alter Mycobacterium tuberculosis transmission inferences

Pathogen genomic data are increasingly used to characterize global and local transmission patterns of important human pathogens and to inform public health interventions. Yet, there is no current consensus on how to measure genomic variation. To test the effect of the variant-identification approach on transmission inferences for Mycobacterium tuberculosis, we conducted an experiment in which five genomic epidemiology groups applied variant-identification pipelines to the same outbreak sequence data. We compared the variants identified by each group in addition to transmission and phylogenetic inferences made with each variant set. To measure the performance of commonly used variant-identification tools, we simulated an outbreak. We compared the performance of three mapping algorithms, five variant callers and two variant filters in recovering true outbreak variants. Finally, we investigated the effect of applying increasingly stringent filters on transmission inferences and phylogenies. We found that variant-calling approaches used by different groups do not recover consistent sets of variants, which can lead to conflicting transmission inferences. Further, performance in recovering true variation varied widely across approaches. While no single variant-identification approach outperforms others in both recovering true genome-wide and outbreak-level variation, variant-identification algorithms calibrated upon real sequence data or that incorporate local reassembly outperform others in recovering true pairwise differences between isolates. The choice of variant filters contributed to extensive differences across pipelines, and applying increasingly stringent filters rapidly eroded the accuracy of transmission inferences and quality of phylogenies reconstructed from outbreak variation. Commonly used approaches to identify M. tuberculosis genomic variation have variable performance, particularly when predicting potential transmission links from pairwise genetic distances. Phylogenetic reconstruction may be improved by less stringent variant filtering. Approaches that improve variant identification in repetitive, hypervariable regions, such as long-read assemblies, may improve transmission inference.

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 bovis: From Genotyping to Genome Sequencing

Mycobacterium bovis is the main pathogen of bovine, zoonotic, and wildlife tuberculosis. Despite the existence of programs for bovine tuberculosis (bTB) control in many regions, the disease remains a challenge for the veterinary and public health sectors, especially in developing countries and in high-income nations with wildlife reservoirs. Current bTB control programs are mostly based on test-and-slaughter, movement restrictions, and post-mortem inspection measures. In certain settings, contact tracing and surveillance has benefited from M. bovis genotyping techniques. More recently, whole-genome sequencing (WGS) has become the preferential technique to inform outbreak response through contact tracing and source identification for many infectious diseases. As the cost per genome decreases, the application of WGS to bTB control programs is inevitable moving forward. However, there are technical challenges in data analyses and interpretation that hinder the implementation of M. bovis WGS as a molecular epidemiology tool. Therefore, the aim of this review is to describe M. bovis genotyping techniques and discuss current standards and challenges of the use of M. bovis WGS for transmission investigation, surveillance, and global lineages distribution. We compiled a series of associated research gaps to be explored with the ultimate goal of implementing M. bovis WGS in a standardized manner in bTB control programs.

Combining genomics and epidemiology to analyse bi-directional transmission of Mycobacterium bovis in a multi-host system

Quantifying pathogen transmission in multi-host systems is difficult, as exemplified in bovine tuberculosis (bTB) systems, but is crucial for control. The agent of bTB, Mycobacterium bovis, persists in cattle populations worldwide, often where potential wildlife reservoirs exist. However, the relative contribution of different host species to bTB persistence is generally unknown. In Britain, the role of badgers in infection persistence in cattle is highly contentious, despite decades of research and control efforts. We applied Bayesian phylogenetic and machine-learning approaches to bacterial genome data to quantify the roles of badgers and cattle in M. bovis infection dynamics in the presence of data biases. Our results suggest that transmission occurs more frequently from badgers to cattle than vice versa (10.4x in the most likely model) and that within-species transmission occurs at higher rates than between-species transmission for both. If representative, our results suggest that control operations should target both cattle and badgers.

Computational pan-genome mapping and pairwise SNP-distance improve detection of Mycobacterium tuberculosis transmission clusters

Next-generation sequencing based base-by-base distance measures have become an integral complement to epidemiological investigation of infectious disease outbreaks. This study introduces PANPASCO, a computational pan-genome mapping based, pairwise distance method that is highly sensitive to differences between cases, even when located in regions of lineage specific reference genomes. We show that our approach is superior to previously published methods in several datasets and across different Mycobacterium tuberculosis lineages, as its characteristics allow the comparison of a high number of diverse samples in one analysis—a scenario that becomes more and more likely with the increased usage of whole-genome sequencing in transmission surveillance.

Tuberculosis still is a threat to global health. It is essential to detect and interrupt transmissions to stop the spread of this infectious disease. With the rising use of next-generation sequencing methods, its application in the surveillance of Mycobacterium tuberculosis has become increasingly important in the last years. The main goal of molecular surveillance is the identification of patient-patient transmission and cluster detection. The mutation rate of M. tuberculosis is very low and stable. Therefore, many existing methods for comparative analysis of isolates provide inadequate results since their resolution is too limited. There is a need for a method that takes every detectable difference into account. We developed PANPASCO, a novel approach for comparing pairs of isolates using all genomic information available for each pair. We combine improved SNP-distance calculation with the use of a pan-genome incorporating more than 100 M. tuberculosis reference genomes representing lineages 1-4 for read mapping prior to variant detection. We thereby enable the collective analysis and comparison of similar and diverse isolates associated with different M. tuberculosis strains.

Dispersal of Mycobacterium tuberculosis Driven by Historical European Trade in the South Pacific

Mycobacterium tuberculosis (Mtb) is a globally distributed bacterial pathogen whose population structure has largely been shaped by the activities of its obligate human host. Oceania was the last major global region to be reached by Europeans and is the last region for which the dispersal and evolution of Mtb remains largely unexplored. Here, we investigated the evolutionary history of the Euro-American L4.4 sublineage and its dispersal to the South Pacific. Using a phylodynamics approach and a dataset of 236 global Mtb L4.4 genomes we have traced the origins and dispersal of L4.4 strains to New Zealand. These strains are predominantly found in indigenous Māori and Pacific people and we identify a clade of European, likely French, origin that is prevalent in indigenous populations in both New Zealand and Canada. Molecular dating suggests the expansion of European trade networks in the early 19th century drove the dispersal of this clade to the South Pacific. We also identify historical and social factors within the region that have contributed to the local spread and expansion of these strains, including recent Pacific migrations to New Zealand and the rapid urbanization of Māori in the 20th century. Our results offer new insight into the expansion and dispersal of Mtb in the South Pacific and provide a striking example of the role of historical European migrations in the global dispersal of Mtb.

Tracking and responding to an outbreak of tuberculosis using MIRU-VNTR genotyping and whole genome sequencing as epidemiological tools

Background

We describe an outbreak that contributed to a near doubling of the incidence of tuberculosis in Southampton, UK. We examine the importance of 24 locus mycobacterial interspersed repetitive unit variable number tandem repeat (MIRU-VNTR) genotyping in its identification and management and the role of whole genome sequencing (WGS) in tracing the spread of the strain.

Methods

Outbreak cases were defined as those diagnosed between January and December 2011 with indistinguishable 24 locus-MIRU-VNTR genotypes or, cases linked epidemiologically. A cluster questionnaire was administered by TB nurses to identify contacts and social settings.

Results

Overall, 25 patients fulfilled the case definition. No cases with this MIRU-VNTR genotype had been detected in the UK previously. Connections were found between all cases through household contacts or social venues including a football club, Internet cafe and barber's shop. Public health actions included extended contact tracing, venue screening and TB awareness-raising. The outbreak resulted in a high rate of transmission and high incidence of clinical disease among contacts.

Conclusions

This outbreak illustrates the value of combining active case-finding with prospective MIRU-VNTR genotyping to identify settings to undertake public health action. In addition WGS revealed that the VNTR-defined cluster was a single outbreak and that active TB transmission not reactivation was responsible for this outbreak in non-UK born individuals.

Deciphering drug resistance in Mycobacterium tuberculosis using whole-genome sequencing: progress, promise, and challenges

Tuberculosis (TB) is a global infectious threat that is intensified by an increasing incidence of highly drug-resistant disease. Whole-genome sequencing (WGS) studies of Mycobacterium tuberculosis, the causative agent of TB, have greatly increased our understanding of this pathogen. Since the first M. tuberculosis genome was published in 1998, WGS has provided a more complete account of the genomic features that cause resistance in populations of M. tuberculosis, has helped to fill gaps in our knowledge of how both classical and new antitubercular drugs work, and has identified specific mutations that allow M. tuberculosis to escape the effects of these drugs. WGS studies have also revealed how resistance evolves both within an individual patient and within patient populations, including the important roles of de novo acquisition of resistance and clonal spread. These findings have informed decisions about which drug-resistance mutations should be included on extended diagnostic panels. From its origins as a basic science technique, WGS of M. tuberculosis is becoming part of the modern clinical microbiology laboratory, promising rapid and improved detection of drug resistance, and detailed and real-time epidemiology of TB outbreaks. We review the successes and highlight the challenges that remain in applying WGS to improve the control of drug-resistant TB through monitoring its evolution and spread, and to inform more rapid and effective diagnostic and therapeutic strategies.

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.

Role and value of whole genome sequencing in studying tuberculosis transmission

BACKGROUND

Tuberculosis (TB) remains a serious public health threat worldwide. Theoretically ultimate resolution of whole genome sequencing (WGS) for Mycobacterium tuberculosis complex (MTBC) strain classification makes this technology very attractive for epidemiological investigations.

OBJECTIVES

To summarize the evidence available in peer-reviewed publications on the role and place of WGS in detection of TB transmission.

SOURCES

A total of 69 peer-reviewed publications identified in Pubmed database.

CONTENT

Evidence from >30 publications suggests that a cut-off value of fewer than six single nucleotide polymorphisms between strains efficiently excludes cases that are not the result of recent transmission and could be used for the identification of drug-sensitive isolates involved in direct human-to-human TB transmission. Sensitivity of WGS to identify epidemiologically linked isolates is high, reaching 100% in eight studies with specificity (17%-95%) highly dependent on the settings. Drug resistance and specific phylogenetic lineages may be associated with accelerated mutation rates affecting genetic distances. WGS can be potentially used to distinguish between true relapses and re-infections but in high-incidence low-diversity settings this would require consideration of epidemiological links and minority alleles. Data from four studies looking into within-host diversity highlight a need for developing criteria for acceptance or rejection of WGS relatedness results depending on the proportion of minority alleles.

IMPLICATIONS

WGS will potentially allow for more targeted public health actions preventing unnecessary investigations of false clusters. Consensus on standardization of raw data quality control processing criteria, analytical pipelines and reporting language is yet to be reached.

Assessment of the use and need for an integrated molecular surveillance of tuberculosis: an online survey in Germany

Background

The implementation of an integrated molecular surveillance (IMS) of tuberculosis (TB) is of high priority for TB control. IMS is defined as the systematic inclusion of molecular typing results in the national TB surveillance system. Although not standardized, an IMS of TB is already implemented in several low TB incidence countries. Germany is in the process of implementing a nationwide IMS of TB. This requires close collaboration between national and local health authorities. We conducted an online survey to understand the current use of molecular typing results for TB surveillance among the local public health offices (PHO)s in Germany, and to collect their perception and expectations towards the implementation of a nationwide IMS of TB.

Methods

The online survey was developed using the software Voxco and included 31 questions. The survey was sent to all the 377 local PHOs in Germany in April 2017. Responses were collected until June 2017.

Results

A total of 174/377 (46.2%) local PHOs participated in our survey, and 88/377 (23.3%) used molecular typing results in their routine TB surveillance work. The PHOs used molecular typing results especially as support for epidemiological contact tracing (62/88, 70.4%). We found statistically significant differences between answers of PHOs that did not use molecular typing results (n = 86) vs. PHOs that did use molecular typing results (n = 88): the latter perceived the use of molecular typing results as more beneficial for their work compared to the former (65.9% vs. 34.9%, p < 0.05). Moreover, the PHOs using molecular typing results expect for the future more support and coordination from regional and national public health institutes, especially regarding the identification and analysis of molecular clusters.

Conclusions

Our study is a step forward in the broader goal of implementing an IMS of TB in Germany. The local PHOs currently using the molecular typing results highlighted their positive attitude towards the implementation of an IMS, but also their needs of more support. Similar assessments might serve as an example for other countries which are on the way to implement a nationwide IMS of TB.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6631-6) contains supplementary material, which is available to authorized users.

Whole-Genome Sequencing of Drug-Resistant Mycobacterium tuberculosis Strains, Tunisia, 2012-2016

To investigate transmission of drug-resistant strains of Mycobacterium tuberculosis in Tunisia, we performed whole-genome sequencing on 46 multidrug-resistant strains isolated during 2012-2016. Core-genome multilocus sequence typing grouped 30 strains (65.2%) into 3 clusters, indicating extensive recent transmission and Haarlem clone predominance. Whole-genome sequencing might help public health services undertake appropriate control actions.

Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data

There exists significant interest in developing statistical and computational tools for inferring 'who infected whom' in an infectious disease outbreak from densely sampled case data, with most recent studies focusing on the analysis of whole genome sequence data. However, genomic data can be poorly informative of transmission events if mutations accumulate too slowly to resolve individual transmission pairs or if there exist multiple pathogens lineages within-host, and there has been little focus on incorporating other types of outbreak data. We present here a methodology that uses contact data for the inference of transmission trees in a statistically rigorous manner, alongside genomic data and temporal data. Contact data is frequently collected in outbreaks of pathogens spread by close contact, including Ebola virus (EBOV), severe acute respiratory syndrome coronavirus (SARS-CoV) and Mycobacterium tuberculosis (TB), and routinely used to reconstruct transmission chains. As an improvement over previous, ad-hoc approaches, we developed a probabilistic model that relates a set of contact data to an underlying transmission tree and integrated this in the outbreaker2 inference framework. By analyzing simulated outbreaks under various contact tracing scenarios, we demonstrate that contact data significantly improves our ability to reconstruct transmission trees, even under realistic limitations on the coverage of the contact tracing effort and the amount of non-infectious mixing between cases. Indeed, contact data is equally or more informative than fully sampled whole genome sequence data in certain scenarios. We then use our method to analyze the early stages of the 2003 SARS outbreak in Singapore and describe the range of transmission scenarios consistent with contact data and genetic sequence in a probabilistic manner for the first time. This simple yet flexible model can easily be incorporated into existing tools for outbreak reconstruction and should permit a better integration of genomic and epidemiological data for inferring transmission chains.

The Evolution of Genotyping Strategies To Detect, Analyze, and Control Transmission of Tuberculosis

The introduction of genotypic tools to analyze Mycobacterium tuberculosis isolates has transformed our knowledge of the transmission dynamics of this pathogen. We discuss the development of the laboratory methods that have been applied in recent years to study the epidemiology of M. tuberculosis. This review integrates two approaches: on the one hand, it considers how genotyping techniques have evolved over the years; and on the other, it looks at how the way we think these techniques should be applied has changed. We begin by examining the application of fingerprinting tools to suspected outbreaks only, before moving on to universal genotyping schemes, and finally we describe the latest real-time strategies used in molecular epidemiology. We also analyze refined approaches to obtaining epidemiological data from patients and to increasing the discriminatory power of genotyping by techniques based on genomic characterization. Finally, we review the development of integrative solutions to reconcile the speed of PCR-based methods with the high discriminatory power of whole-genome sequencing in easily implemented formats adapted to low-resource settings. Our analysis of future considerations highlights the need to bring together the three key elements of high-quality surveillance of transmission in tuberculosis, namely, speed, precision, and ease of implementation.

Statistical Method to Detect Tuberculosis Outbreaks among Endemic Clusters in a Low-Incidence Setting

We previously reported use of genotype surveillance data to predict outbreaks among incident tuberculosis clusters. We propose a method to detect possible outbreaks among endemic tuberculosis clusters. We detected 15 possible outbreaks, of which 10 had epidemiologic data or whole-genome sequencing results. Eight outbreaks were corroborated.

First insights on the genetic diversity of MDR Mycobacterium tuberculosis in Lebanon

Background

Lebanon hosts a heterogeneous population coming from underdeveloped and developing countries, resulting in increasing incidences of tuberculosis over the past years. The genetic heterogeneity and lineages associated with tuberculosis, along with their resistance determinants have not been studied at the genomic level previously in the region.

Methods

Isolates were recovered from the American University of Beirut Medical Center (AUBMC). Antimicrobial susceptibility profiles were determined using the MGIT automated system for the first-line drugs at AUBMC, while second-line drug susceptibility was tested at Mayo Clinic Laboratories. Whole Genome Sequencing (WGS) was performed to classify mycobacterial lineages and highlight single nucleotide mutations causing resistance to both 1st line and 2nd line antimicrobials. wgSNP analysis provided insights on the phylogeny of the isolates along with spoligotyping and core genomic SNVs, IS6110 insertion sites, and variable number tandem repeats (VNTR).

Results

The analyzed isolates carry distinct resistance determinants to isoniazid, rifampicin, ethambutol, quinolones, and streptomycin. The isolates belonged to different lineages including the Euro/American lineage (Lineage 4) (53.8%), M. bovis (15.4%) and Delhi/Central Asia (Lineage 1) (15.4%), Beijing/East Asia (Lineage 2) (7.7%), and East Africa/Indian Ocean lineage (Lineage 3) (7.7%) showing great phylogenetic differences at the genomic level.

Conclusions

The population diversity in Lebanon holds an equally diverse and uncharacterized population of drug resistant mycobacteria. To achieve the WHO “END-TB” milestones of 2025 and 2035, Lebanon must decrease TB incidences by 95% in the next decade. This can only be done through WGS-based patient centered diagnosis with higher throughput and genomic resolution to improve treatment outcomes and to monitor transmission patterns.

Electronic supplementary material

The online version of this article (10.1186/s12879-018-3626-3) contains supplementary material, which is available to authorized users.

Spatial Patterns of Extensively Drug-Resistant Tuberculosis Transmission in KwaZulu-Natal, South Africa

Background

Transmission is driving the global drug-resistant tuberculosis (TB) epidemic; nearly three-quarters of drug-resistant TB cases are attributable to transmission. Geographic patterns of disease incidence, combined with information on probable transmission links, can define the spatial scale of transmission and generate hypotheses about factors driving transmission patterns.

Methods

We combined whole-genome sequencing data with home Global Positioning System coordinates from 344 participants with extensively drug-resistant (XDR) TB in KwaZulu-Natal, South Africa, diagnosed from 2011 to 2014. We aimed to determine if genomically linked (difference of ≤5 single-nucleotide polymorphisms) cases lived close to one another, which would suggest a role for local community settings in transmission.

Results

One hundred eighty-two study participants were genomically linked, comprising 1084 case-pairs. The median distance between case-pairs' homes was 108 km (interquartile range, 64-162 km). Between-district, as compared to within-district, links accounted for the majority (912/1084 [84%]) of genomic links. Half (526 [49%]) of genomic links involved a case from Durban, the urban center of KwaZulu-Natal.

Conclusions

The high proportions of between-district links with Durban provide insight into possible drivers of province-wide XDR-TB transmission, including urban-rural migration. Further research should focus on characterizing the contribution of these drivers to overall XDR-TB transmission in KwaZulu-Natal to inform design of targeted strategies to curb the drug-resistant TB epidemic.

The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology

BACKGROUND

Tracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult.

METHODS

This study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005-2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated.

FINDINGS

Our results suggest that clusters based on Spoligotyping could encompass transmission events that occurred almost 200 years prior to sampling while 24-loci-MIRU-VNTR often represented three decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events, e.g. in timespans of up to 10 years for a 5 SNP/allele cut-off.

INTERPRETATION

With the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting.

Whole Genome Sequencing for Determining the Source of Mycobacterium bovis Infections in Livestock Herds and Wildlife in New Zealand

The ability to DNA fingerprint Mycobacterium bovis isolates helped to define the role of wildlife in the persistence of bovine tuberculosis in New Zealand. DNA fingerprinting results currently help to guide wildlife control measures and also aid in tracing the source of infections that result from movement of livestock. During the last 5 years we have developed the ability to distinguish New Zealand (NZ) M. bovis isolates by comparing the sequences of whole genome sequenced (WGS) M. bovis samples. WGS provides much higher resolution than our other established typing methods and greatly improves the definition of the regional localization of NZ M. bovis types. Three outbreak investigations are described and results demonstrate how WGS analysis has led to the confirmation of epidemiological sourcing of infection, to better definition of new sources of infection by ruling out other possible sources, and has revealed probable wildlife infection in an area considered to be free of infected wildlife. The routine use of WGS analyses for sourcing new M. bovis infections will be an important component of the strategy employed to eradicate bovine TB from NZ livestock and wildlife.

Global expansion of Mycobacterium tuberculosis lineage 4 shaped by colonial migration and local adaptation

On the basis of population genomic and phylogeographic analyses of 1669 Mycobacterium tuberculosis lineage 4 (L4) genomes, we find that dispersal of L4 has been completely dominated by historical migrations out of Europe. We demonstrate an intimate temporal relationship between European colonial expansion into Africa and the Americas and the spread of L4 tuberculosis (TB). Markedly, in the age of antibiotics, mutations conferring antimicrobial resistance overwhelmingly emerged locally (at the level of nations), with minimal cross-border transmission of resistance. The latter finding was found to reflect the relatively recent emergence of these mutations, as a similar degree of local restriction was observed for susceptible variants emerging on comparable time scales. The restricted international transmission of drug-resistant TB suggests that containment efforts at the level of individual countries could be successful.

Epidemiological and genomic determinants of tuberculosis outbreaks in First Nations communities in Canada

BACKGROUND

In Canada, tuberculosis disproportionately affects foreign-born and First Nations populations. Within First Nations' peoples, a high proportion of cases occur in association with outbreaks. Tuberculosis transmission in the context of outbreaks is thought to result from the convergence of several factors including characteristics of the cases, contacts, the environment, and the pathogen.

METHODS

We examined the epidemiological and genomic determinants of two well-characterized tuberculosis outbreaks attributed to two super-spreaders among First Nations in the province of Alberta. These outbreaks were associated with two distinct DNA fingerprints (restriction fragment-length polymorphisms or RFLPs 0.0142 and 0.0728). We compared outbreak isolates with endemic isolates not spatio-temporarily linked to outbreak cases. We extracted epidemiological variables pertaining to tuberculosis cases and contacts from individual public health records and the provincial tuberculosis registry. We conducted group analyses using parametric and non-parametric statistical tests. We carried out whole-genome sequencing and bioinformatic analysis using validated protocols.

RESULTS

We observed differences between outbreak and endemic groups in the mean number of total and child-aged contacts and the number of contacts with new positive and converted tuberculin skin tests in all group comparisons (p < 0.05). Differences were also detected in the proportion of cases with cavitation on a chest radiograph and the mean number of close contacts in selected group comparisons (p < 0.02). A phylogenetic network analysis of whole-genome sequencing data indicated that most outbreak and endemic strains were closely related to the source case for the 0.0142 fingerprint. For the 0.0728 fingerprint, the source case haplotype was circulating among endemic cases prior to the outbreak. Genetic and temporal distances were not correlated for either RFLP 0.0142 (r² = - 0.05) or RFLP 0.0728 (r² = 0.09) when all isolates were analyzed.

CONCLUSIONS

We found no evidence that endemic strains acquired mutations resulting in their emergence in outbreak form. We conclude that the propagation of these outbreaks was likely driven by the combination of characteristics of the source cases, contacts, and the environment. The role of whole-genome sequencing in understanding mycobacterial evolution and in assisting public health authorities in conducting contact investigations and managing outbreaks is important and expected to grow in the future.

The use of whole-genome sequencing in cluster investigation of a multidrug-resistant tuberculosis outbreak

We used whole-genome sequencing (WGS) to delineate transmission networks and investigate the benefits of WGS during cluster investigation.We included clustered cases of multidrug-resistant (MDR) tuberculosis (TB)/extensively drug-resistant (XDR) TB linked by mycobacterial interspersed repetitive unit variable tandem repeat (MIRU-VNTR) strain typing or epidemiological information in the national cluster B1006, notified between 2007 and 2013 in the UK. We excluded from further investigation cases whose isolates differed by greater than 12 single nucleotide polymorphisms (SNPs). Data relating to patients' social networks were collected.27 cases were investigated and 22 had WGS, eight of which (36%) were excluded as their isolates differed by more than 12 SNPs to other cases. 18 cases were ruled into the transmission network based on genomic and epidemiological information. Evidence of transmission was inconclusive in seven out of 18 cases (39%) in the transmission network following WGS and epidemiological investigation.This investigation of a drug-resistant TB cluster illustrates the opportunities and limitations of WGS in understanding transmission in a setting with a high proportion of migrant cases. The use of WGS should be combined with classical epidemiological methods. However, not every cluster will be solvable, regardless of the quality of genomic data.

Automated IS6110-based fingerprinting of Mycobacterium tuberculosis: Reaching unprecedented discriminatory power and versatility

BACKGROUND

Several technical hurdles and limitations have restricted the use of IS6110 restriction fragment length polymorphism (IS6110 RFLP), the most effective typing method for detecting recent tuberculosis (TB) transmission events. This has prompted us to conceive an alternative modality, IS6110-5'3'FP, a plasmid-based cloning approach coupled to a single PCR amplification of differentially labeled 5' and 3' IS6110 polymorphic ends and their automated fractionation on a capillary sequencer. The potential of IS6110-5'3'FP to be used as an alternative to IS6110 RFLP has been previously demonstrated, yet further technical improvements are still required for optimal discriminatory power and versatility.

OBJECTIVES

Here we introduced critical amendments to the original IS6110-5'3'FP protocol and compared its performance to that of 24-loci multiple interspersed repetitive unit-variable number tandem repeats (MIRU-VNTR), the current standard method for TB transmission analyses.

METHODS

IS6110-5'3'FP protocol modifications involved: (i) the generation of smaller-sized polymorphic fragments for efficient cloning and PCR amplification, (ii) omission of the plasmid amplification step in E. coli for shorter turnaround times, (iii) the use of more stable fluorophores for increased sensitivity, (iv) automated subtraction of background fluorescent signals, and (v) the automated conversion of fluorescent peaks into binary data.

RESULTS

In doing so, the overall turnaround time of IS6110-5'3'FP was reduced to 4 hours. The new protocol allowed detecting almost all 5' and 3' IS6110 polymorphic fragments of any given strain, including IS6110 high-copy number Beijing strains. IS6110-5'3'FP proved much more discriminative than 24-loci MIRU-VNTR, particularly with strains of the M. tuberculosis lineage 4.

CONCLUSIONS

The IS6110-5'3'FP protocol described herein reached the optimal discriminatory potential of IS6110 fingerprinting and proved more accurate than 24-loci MIRU-VNTR in estimating recent TB transmission. The method, which is highly cost-effective, was rendered versatile enough to prompt its evaluation as an automatized solution for a TB integrated molecular surveillance.

Use of whole genome sequencing in surveillance of drug resistant tuberculosis

INTRODUCTION

The threat of resistance to anti-tuberculosis drugs is of global concern. Current efforts to monitor resistance rely on phenotypic testing where cultured bacteria are exposed to critical concentrations of the drugs. Capacity for such testing is low in TB endemic countries. Drug resistance is caused by mutations in the Mycobacterium tuberculosis genome and whole genome sequencing to detect these mutations offers an alternative means of assessing resistance. Areas covered: The challenges of assessing TB drug resistance are discussed. Progress in elucidating the M. tuberculosis resistome and evidence of the accuracy of next generation sequencing for detecting resistance is reviewed. Expert Commentary: There are considerable advantages to using next generation sequencing for TB drug resistance surveillance. Accuracy is high for detecting resistance to the major first-line drugs but is currently lower for the second-line drugs due to our incomplete knowledge regarding resistance causing mutations. With the advances in sequencing technology and the opportunity to replace phenotypic drug susceptibility testing with safer and more cost effective methods it would appear that the question is when to implement. Current bottlenecks are sample extraction to allow whole genome sequencing directly from sputum and the lack of bioinformatics expertise in some TB endemic countries.