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

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.

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

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

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Whole Genome Sequencing in the Management of Non-Tuberculous Mycobacterial Infections

Infections caused by non-tuberculous mycobacteria (NTM) have been a public health problem in recent decades and contribute significantly to the clinical and economic burden globally. The diagnosis of infections is difficult and time-consuming and, in addition, the conventional diagnostics tests do not have sufficient discrimination power in species identification due to cross-reactions and not fully specific probes. However, technological advances have been made and the whole genome sequencing (WGS) method has been shown to be an essential part of routine diagnostics in clinical mycobacteriology laboratories. The use of this technology has contributed to the characterization of new species of mycobacteria, as well as the identification of gene mutations encoding resistance and virulence factors. Sequencing data also allowed to track global outbreaks of nosocomial NTM infections caused by M. abscessus complex and M. chimaera. To highlight the utility of WGS, we summarize recent scientific studies on WGS as a tool suitable for the management of NTM-induced infections in clinical practice.

Tuberculosis in Adolescents and Young Adults: Emerging Data on TB Transmission and Prevention among Vulnerable Young People

Adolescents and young adults (AYA, ages 10-24 years) comprise a uniquely important but understudied population in global efforts to end tuberculosis (TB), the leading infectious cause of death by a single agent worldwide prior to the COVID-19 pandemic. While TB prevention and care strategies often overlook AYA by grouping them with either children or adults, AYA have particular physiologic, developmental, and social characteristics that require dedicated approaches. This review describes current evidence on the prevention and control of TB among AYA, including approaches to TB screening, dynamics of TB transmission among AYA, and management challenges within the context of unique developmental needs. Challenges are considered for vulnerable groups of AYA such as migrants and refugees; AYA experiencing homelessness, incarceration, or substance use; and AYA living with HIV. We outline areas for needed research and implementation strategies to address TB among AYA globally.

Developing National Genotype-Independent Indicators for Recent Mycobacterium Tuberculosis Transmission Using Pediatric Cases-United States, 2011-2017

INTRODUCTION

Pediatric tuberculosis (TB) cases are sentinel events for Mycobacterium tuberculosis transmission in communities because children, by definition, must have been infected relatively recently. However, these events are not consistently identified by genotype-dependent surveillance alerting methods because many pediatric TB cases are not culture-positive, a prerequisite for genotyping.

METHODS

We developed 3 potential indicators of ongoing TB transmission based on identifying counties in the United States with relatively high pediatric (aged <15 years) TB incidence: (1) a case proportion indicator: an above-average proportion of pediatric TB cases among all TB cases; (2) a case rate indicator: an above-average pediatric TB case rate; and (3) a statistical model indicator: a statistical model based on a significant increase in pediatric TB cases from the previous 8-quarter moving average.

RESULTS

Of the 249 US counties reporting ≥2 pediatric TB cases during 2009-2017, 240 and 249 counties were identified by the case proportion and case rate indicators, respectively. The statistical model indicator identified 40 counties with a significant increase in the number of pediatric TB cases. We compared results from the 3 indicators with an independently generated list of 91 likely transmission events involving ≥2 pediatric cases (ie, known TB outbreaks or case clusters with reported epidemiologic links). All counties with likely transmission events involving multiple pediatric cases were identified by ≥1 indicator; 23 were identified by all 3 indicators.

PRACTICE IMPLICATIONS

This retrospective analysis demonstrates the feasibility of using routine TB surveillance data to identify counties where ongoing TB transmission might be occurring, even in the absence of available genotyping data.

Molecular Epidemiological Information System to Support Management of Multidrug-Resistant Tuberculosis in Thailand: Abstract

OBJECTIVE

To support the End TB strategy with an informatics system that integrates genomic data and the geographic information system (GIS) of Mycobacterium tuberculosis (MTB) clinical isolates. We aim to develop a system prototype for implementing genomic data to support multiple drug-resistant tuberculosis (MDR-TB) control.

METHODS

A 12-step data value chain was applied to describe the information flow within the system. A prototyping-oriented system development method was utilized to test the feasibility of certain technical aspects of a system, and as specification tools to determine user requirements. A simulated dataset was entered as input for initial system testing.

RESULTS

System prototype, namely Integrated MOL Outbreak detection and Joint investigation (iMoji), was established. The data entry modules consisted of (1) patient registration, (2) sample registration, (3) laboratory data entry and data analysis, and (4) verification and approval of the analyzed data. The initial system test demonstrated connectivity among modules without error. The system was able to report integrated genomic data and GIS information of MDR-TB for clustering analysis.

CONCLUSION

iMoji provides an interactive model for determining molecular epidemiological links of MDR-TB and corresponding spatial information to guide public health interventions for tuberculosis control.

Comparison of routine field epidemiology and whole genome sequencing to identify tuberculosis transmission in a remote setting

Yukon Territory (YT) is a remote region in northern Canada with ongoing spread of tuberculosis (TB). To explore the utility of whole genome sequencing (WGS) for TB surveillance and monitoring in a setting with detailed contact tracing and interview data, we used a mixed-methods approach. Our analysis included all culture-confirmed cases in YT (2005-2014) and incorporated data from 24-locus Mycobacterial Interspersed Repetitive Units-Variable Number of Tandem Repeats (MIRU-VNTR) genotyping, WGS and contact tracing. We compared field-based (contact investigation (CI) data + MIRU-VNTR) and genomic-based (WGS + MIRU-VNTR + basic case data) investigations to identify the most likely source of each person's TB and assessed the knowledge, attitudes and practices of programme personnel around genotyping and genomics using online, multiple-choice surveys (n = 4) and an in-person group interview (n = 5). Field- and genomics-based approaches agreed for 26 of 32 (81%) cases on likely location of TB acquisition. There was less agreement in the identification of specific source cases (13/22 or 59% of cases). Single-locus MIRU-VNTR variants and limited genetic diversity complicated the analysis. Qualitative data indicated that participants viewed genomic epidemiology as a useful tool to streamline investigations, particularly in differentiating latent TB reactivation from the recent transmission. Based on this, genomic data could be used to enhance CIs, focus resources, target interventions and aid in TB programme evaluation.

A tuberculosis school outbreak in China, 2018: reaching an often overlooked adolescent population

Adolescents have been largely neglected from tuberculosis control efforts. In low- to medium burden settings much of the tuberculosis burden in this age group occurs from school outbreaks. We report on a large tuberculosis outbreak in adolescents from a boarding high school in Jiangsu Province, China. From March to June 2018, a tuberculosis outbreak occurred in a boarding high school. We conducted an outbreak investigation involving clinical diagnostic tests and molecular analysis to determine the outbreak origin. Cases were detected through symptom screening, tuberculin skin testing (TST), chest radiography, sputum smear, solid sputum culture and GeneXpert MTB/RIF. Mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) genotyping and spoligotyping methods were performed on Mycobacterium tuberculosis (M. tuberculosis) isolates to identify the outbreak origin. A total of 845 students and 131 teachers/staff attended a TST screening for tuberculosis infection. The prevalence of elevated tuberculin reactions at ≥5, ≥10 and ≥15 mm was 12.19% (119/976), 6.35% (62/976) and 3.28% (32/976), respectively. Radiographic abnormalities were present in 5.73% (56 of 976) individuals, 40 students and 16 teachers/staff. Of these, 12 students were diagnosed with confirmed tuberculosis. In total, 14 students (two index cases and 12 confirmed cases) were diagnosed and reported in the tuberculosis outbreak, an attack rate of 1.7% (14/847) among students (two index cases and 845 screened students). Results from MIRU-VNTR typing and spoligotyping analyses demonstrated that three M. tuberculosis strains belong to the Beijing family with corresponding MIRU-VNTR alleles. This school-based tuberculosis outbreak among adolescents demonstrates that transmission among individuals in this age group is common and must be prioritised. It suggests that identifying and timely diagnosis of smear-positive cases, especially in the early phase of outbreaks, is the key to preventing further spread among close contacts.

Creating a web-based electronic tool to aid tuberculosis (TB) cluster investigation: data integration in TB surveillance activities in the United Kingdom, 2013 to 2016

Molecular technology to identify relatedness between Mycobacterium tuberculosis complex isolates, representative of possible tuberculosis (TB) transmission between individuals, continues to evolve. At the same time, tools to utilise this information for public health action to improve TB control should also be implemented. Public Health England developed the Strain Typing Module (STM) as an integral part of the web-based surveillance system used in the United Kingdom following the roll-out of prospective 24 loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) strain typing. The creation of such a system required data integration and linkage, bringing together laboratory results and patient notification information. The STM facilitated widespread access to patient strain typing and clustering results for the public health community working in TB control. In addition, the system provided a log of cluster review and investigation decision making and results. Automated real-time data linkage between laboratory and notification data are essential to allow routine use of genotyping results in TB surveillance and control. Outputs must be accessible by those working in TB control at a local level to have any impact in ongoing public health activity.

Whole-Genome Sequencing as Tool for Investigating International Tuberculosis Outbreaks: A Systematic Review

Background: Whole-genome sequencing (WGS) can support the investigation of tuberculosis (TB) outbreaks. The technique has been applied to estimate the timing and directionality of transmission and to exclude cases from an investigation. This review assesses how WGS was applied in international outbreak investigations and discusses the advantages and challenges of the application of WGS.

Methods: Databases were searched for reports on international TB outbreak investigations. Information was extracted on: Why was WGS applied?; How was WGS applied?; Organizational issues; WGS methodology; What was learned/what were the implications of the WGS investigation?; and challenges and lessons learned.

Results: Three studies reporting on international outbreak investigations were identified. Retrospective WGS sequencing was performed in all studies and prospective typing in two to study TB transmission. In one study, WGS data were produced centrally (i.e., in one laboratory) and analysis was done centrally. In two studies, WGS data production was done in a decentralized manner, and analysis was centralized in one laboratory. Three groups of professionals were involved in the international outbreak investigation: public health authorities, laboratory experts, and clinicians. The reported WGS methodology applied differed between the studies in some aspects, e.g., sequencing platform; quality measures, percentage of the reference genome covered, and the mean genomic coverage; analysis, use of a reference genome or de novo assembly; and software used for alignment and analysis. In all three studies, in-house scripts were used for variance calling, and the single nucleotide polymorphism (SNP) approach was used for analysis. All outbreak investigation reports stated that WGS refuted suspected transmission events and provided supporting evidence for epidemiological data. Several challenges were reported of which most were not related to WGS. The only challenge related to WGS was the timeframe of getting WGS data if WGS is not routinely performed.

Conclusions: WGS was considered a useful addition in international TB outbreak investigations. Further standardization of the WGS methodology and good structures for international collaboration and coordination are needed to take full advantage of this new technology. Whether the use of WGS results in earlier detection of cases and thus limits transmission still needs to be determined.

Mycobacterium simiae pulmonary disease in Iran: systematic review and meta-analysis

Mycobacterium simiae is one of the most common nontuberculous mycobacteria (NTM) microorganisms causing lung disease in many countries in the world. A reliable estimate of the extent of M. simiae pulmonary disease has not been well investigated in Iran. We systematically searched multiple databases to identify relative studies. Studies were excluded if they did not use the American Thoracic Society (ATS) and Infectious Diseases Society of America (IDSA) diagnostic criteria for NTM diseases. Data were extracted independently and in duplicate. We assessed pooled estimate by using a random model effect, and sources of heterogeneity were assessed by using Cochran's Q and the I 2 statistic. The potential for publication bias was explored by using Begg's and Egger's tests. All analyses were conducted with Stata 14.0 (StataCorp, College Station, TX, USA). Of 172 articles identified, seven met the inclusion criteria. Of 355 patients who were culture positive for NTM, 82 had M. simiae pulmonary disease according to the ATS/IDSA diagnostic criteria. The pooled frequency of M. simiae pulmonary disease among patients with NTM was 25.0% (95% confidence interval, 16.8-33.2). No evidence of publication bias was observed among the included studies (p >0.05 for Begg's and Egger's tests). Clinical isolates of M. simiae are increasingly being recognized as a cause of pulmonary disease in Iran and need further attention by health authorities.

High genetic diversity among Mycobacterium tuberculosis strains in Tehran, Iran

INTRODUCTION

Tuberculosis (TB) still remains an important public health problem in Iran. The genotyping of Mycobacterium tuberculosis isolates is expected to lead to a better understanding of M. tuberculosis transmission in Tehran, the most populated city of Iran.

MATERIALS AND METHODS

A total of 2300 clinical specimens were obtained from TB suspected patients who were referred to a TB center in Tehran from Jan 2014 to Dec 2016. Identification was performed using both conventional and molecular methods. The presence of resistance to rifampicin was examined by the GeneXpert MTB/RIF. The standard 15-locus mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) typing method was applied to genotype of clinical isolates.

RESULTS

Of 2300 specimens, 80 isolates were identified as M. tuberculosis by using biochemical and molecular tests. Of 80 M. tuberculosis isolates, 76 (95%) had unique genotypic profiles and 4 (5%) shared a profile with one or more other strains. Based on single loci variation (SLV) 4 clonal complexes were observed. NEW-1 was found to be the most predominant lineage (22.5%) followed by West African (1.25%), Central Asian (CAS)/Delhi (1.25%), Bovis (1.25%), H37Rv (1.25%) and multiple matches (1.25%). Loci MIRU10, MIRU26, MTUB21 and QUB26 were found as highly discriminative. No mutation was detected in the hotspot region of rifampicin by using GeneXpert MTB/RIF.

CONCLUSIONS

Our study findings show that there was considerable genotypic diversity among M. tuberculosis isolates in Tehran. The 15-locus MIRU-VNTR showed high HGDI and could be used as a first-line genotyping method for epidemiological studies.