Investigation of a rapidly spreading tuberculosis outbreak using whole-genome sequencing

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.

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 %).

Pathways of TB Transmission in Children-A Systematic Review of Molecular Epidemiological Studies

The widespread paradigm that younger children usually do not transmit M. tuberculosis complex (Mtbc) to their contacts has not yet been proven by genotypically confirmed transmissions. Therefore, we undertook a systematic review of molecular-epidemiological studies to investigate documented source and secondary TB (tuberculosis) cases among children. We searched the literature published before August 2022 using PubMed, Cochrane, and Google Scholar databases. PRISMA statement was used for systematic review. Of 312 records retrieved, 39 studies including children aged below 15 years offered epidemiological links between cluster members. In the 39 studies from 16 countries, 225 children were reported as cluster members of whom the overwhelming majority were infected by adults. Only 3 children-of those were 2 children aged below 10-were reported to be the definite source cases of 11 other children and 1 adult with genotypically matched Mtbc isolates. To date, molecular-epidemiological studies involving children with verified transmission links are scarce. As far as the heterogeneity of the studies we identified allows, we could conclude that the results confirm the paradigm that children aged below 10 hardly ever transmit Mtbc to others. The true extent of TB transmission through children may, however, be underestimated by those selected studies.

Quantifying Mycobacterium tuberculosis Transmission Dynamics Across Global Settings: A Systematic Analysis

The degree to which individual heterogeneity in the production of secondary cases ("superspreading") affects tuberculosis (TB) transmission has not been systematically studied. We searched for population-based or surveillance studies in which whole genome sequencing was used to estimate TB transmission and in which the size distributions of putative TB transmission clusters were enumerated. We fitted cluster-size-distribution data to a negative binomial branching process model to jointly infer the transmission parameters $R$ (the reproduction number) and the dispersion parameter, $k$, which quantifies the propensity of superspreading in a population (generally, lower values of $k$ ($<1.0$) suggest increased heterogeneity). Of 4,796 citations identified in our initial search, 9 studies from 8 global settings met the inclusion criteria (n = 5 studies of all TB; n = 4 studies of drug-resistant TB). Estimated $R$ values (range, 0.10-0.73) were below 1.0, consistent with declining epidemics in the included settings; estimated $k$ values were well below 1.0 (range, 0.02-0.48), indicating the presence of substantial individual-level heterogeneity in transmission across all settings. We estimated that a minority of cases (range, 2%-31%) drive the majority (80%) of ongoing TB transmission at the population level. Identifying sources of heterogeneity and accounting for them in TB control may have a considerable impact on mitigating TB transmission.

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

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

Clinical utility of target amplicon sequencing test for rapid diagnosis of drug-resistant Mycobacterium tuberculosis from respiratory specimens

An in-house-developed target amplicon sequencing by next-generation sequencing technology (TB-NGS) enables simultaneous detection of resistance-related mutations in Mycobacterium tuberculosis (MTB) against 8 anti-tuberculosis drug classes. In this multi-center study, we investigated the clinical utility of incorporating TB-NGS for rapid drug-resistant MTB detection in high endemic regions in southeast China. From January 2018 to November 2019, 4,047 respiratory specimens were available from patients suffering lower respiratory tract infections in Hong Kong and Guangzhou, among which 501 were TB-positive as detected by in-house IS6110-qPCR assay with diagnostic sensitivity and specificity of 97.9 and 99.2%, respectively. Preliminary resistance screening by GenoType MTBDRplus and MTBDRsl identified 25 drug-resistant specimens including 10 multidrug-resistant TB. TB-NGS was performed using MiSeq on all drug-resistant specimens alongside 67 pan-susceptible specimens, and demonstrated 100% concordance to phenotypic drug susceptibility test. All phenotypically resistant specimens with dominating resistance-related mutations exhibited a mutation frequency of over 60%. Three quasispecies were identified with mutation frequency of less than 35% among phenotypically susceptible specimens. They were well distinguished from phenotypically resistant cases and thus would not complicate TB-NGS results interpretations. This is the first large-scale study that explored the use of laboratory-developed NGS platforms for rapid TB diagnosis. By incorporating TB-NGS with our proposed diagnostic algorithm, the workflow would provide a user-friendly, cost-effective routine diagnostic solution for complicated TB cases with an average turnaround time of 6 working days. This is critical for timely management of drug resistant TB patients and expediting public health control on the emergence of drug-resistant TB.

The MtZ Strain: Molecular Characteristics and Outbreak Investigation of the Most Successful Mycobacterium tuberculosis Strain in Aragon Using Whole-Genome Sequencing

Since 2004, a tuberculosis surveillance protocol has been carried out in Aragon, thereby managing to detect all tuberculosis outbreaks that take place in the community. The largest outbreak was caused by a strain named Mycobacterium tuberculosis Zaragoza (MtZ), causing 242 cases as of 2020. The main objective of this work was to analyze this outbreak and the molecular characteristics of this successful strain that could be related to its greater transmission. To do this, we first applied whole-genome sequencing to 57 of the isolates. This revealed two principal transmission clusters and six subclusters arising from them. The MtZ strain belongs to L4.8 and had eight specific single nucleotide polymorphisms (SNPs) in genes considered to be virulence factors [ptpA, mc3D, mc3F, VapB41, pks15 (two SNPs), virS, and VapC50]. Second, a transcriptomic study was carried out to better understand the multiple IS6110 copies present in its genome. This allowed us to observe three effects of IS6110: the disruption of the gene in which the IS6110 is inserted (desA3), the overexpression of a gene (ppe38), and the absence of transcription of genes (cut1:Rv1765c) due to the recombination of two IS6110 copies. Finally, because of the disruption of ppe38 and ppe71 genes by an IS6110, a study of PE_PGRS secretion was carried out, showing that MtZ secretes these factors in higher amounts than the reference strain, thereby differing from the hypervirulent phenotype described for the Beijing strains. In conclusion, MtZ consists of several SNPs in genes related to virulence, pathogenesis, and survival, as well as other genomic polymorphisms, which may be implicated in its success among our population.

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.

In-depth Analysis of IS6110 Genomic Variability in the Mycobacterium tuberculosis Complex

The insertion sequence (IS) 6110 is a repetitive mobile element specific for the Mycobacterium tuberculosis complex (MTBC) used for years to diagnose and genotype this pathogen. It contains the overlapping reading frames orfA and orfB that encode a transposase. Its genetic variability is difficult to study because multiple copies are present in the genome. IS6110 is randomly located, nevertheless some preferential locations have been reported, which could be related to the behaviour of the strains. The aim of this work was to determine the intra- and inter-strain genetic conservation of this element in the MTBC. For this purpose, we analysed 158 sequences of IS6110 copies from 55 strains. Eighty-four copies were from 17 strains for which we knew all the locations in their genome. In addition, we studied 74 IS6110 copies in 38 different MTBC strains in which the location was characteristic of different families including Haarlem, LAM, S, and L6 strains. We observed mutation in 13.3% of the copies studied and we found 10 IS6110 variants in 21 copies belonging to 16 strains. The high copy number strains showed 6.2% of their IS6110 copies mutated, in contrast with the 31.1% in the low-copy-number strains. The apparently more ancient copy localised in the DR region was that with more variant copies, probably because this was the most studied location. Notably, all Haarlem and X family strains studied have an IS6110 in Rv0403c, suggesting a common origin for both families. Nevertheless, we detected a variant specific for the X family that would have occurred in this location after the phylogenetic separation. This variant does not prevent transposition although it may occur at a lower frequency, as X strains remain with low copy number (LCN) of IS6110.

A Whole-Genome Sequencing-Based Study to Delineate the Risk and Characteristics of Tuberculosis Transmission in an Insular Population Over 10 Years in Shanghai

Background

Tuberculosis (TB) has remained a tough problem in China. This study aims to identify the risk of tuberculosis transmission and to assess its characteristics.

Methods

We performed a molecular epidemiological study for patients with culture-positive Mycobacterium tuberculosis (M. tuberculosis) in Shanghai, from 2009 to 2018. Demographic information was obtained from the Tuberculosis Information Management System. Whole-genome sequencing (WGS) was conducted with a threshold of 12 single-nucleotide polymorphisms (SNPs) to distinguish the genomic cluster. To analyze the characteristics of TB transmission, the contact investigation for clustered cases was performed.

Results

In total, 94 (27.25%) of the 345 enrolled patients were grouped into 42 genomic clusters, indicating local transmission of M. tuberculosis strains. Compared to a health system delay <14 days, patients with a health system delay ≥14 days [adjusted odds ratios (AOR) = 2.57, 95% confidence interval (CI): 1.34–4.95] were more likely to be clustered. Patients under 65 years old (AOR = 3.11, 95% CI: 1.76–5.49), residents (AOR = 2.43, 95% CI: 1.18–4.99), and Beijing genotype strains (AOR = 3.35, 95% CI: 1.32–8.53) were associated with increased risk of clustering. Interestingly, patients with resistance to isoniazid (AOR = 2.36, 95% CI: 1.15–4.88) had a higher risk of transmission. Sixteen confirmed/probable epidemiological links were identified. Local transmission of imported cases and household transmission were prominent.

Conclusion

Health system delay is a crucial factor for TB transmission. Patients with resistance to isoniazid should be priority targets for contact investigation to reduce transmission.

Logically Inferred Tuberculosis Transmission (LITT): A Data Integration Algorithm to Rank Potential Source Cases

Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the integration and analysis of whole-genome sequencing, clinical, and epidemiological data. Based on the work typically performed by hand during a cluster investigation, LITT identifies and ranks potential source cases for each case in a TB cluster. We evaluated LITT using a diverse dataset of 534 cases in 56 clusters (size range: 2–69 cases), which were investigated locally in three different U.S. jurisdictions. Investigators and LITT agreed on the most likely source case for 145 (80%) of 181 cases. By reviewing discrepancies, we found that many of the remaining differences resulted from errors in the dataset used for the LITT algorithm. In addition, we developed a graphical user interface, user's manual, and training resources to improve LITT accessibility for frontline staff. While LITT cannot replace thorough field investigation, the algorithm can help investigators systematically analyze and interpret complex data over the course of a TB cluster investigation.

Code available at:https://github.com/CDCgov/TB_molecular_epidemiology/tree/1.0; https://zenodo.org/badge/latestdoi/166261171.

Transmission of tuberculosis between foreign-born and Finnish-born populations in Finland, 2014-2017

We describe the epidemiology of tuberculosis (TB) and characterized Mycobacterium tuberculosis (M. tuberculosis) isolates to evaluate transmission between foreign-born and Finnish-born populations. Data on TB cases were obtained from the National Infectious Disease Register and denominator data on legal residents and their country of birth from the Population Information System. M. tuberculosis isolates were genotyped by spoligotyping and Mycobacterial Interspersed Repetitive Unit Variable Number Tandem Repeat (MIRU-VNTR). We characterized clusters by age, sex, origin and region of living which included both foreign-born cases and those born in Finland. During 2014-2017, 1015 TB cases were notified; 814 were confirmed by culture. The proportion of foreign-born cases increased from 33.3% to 39.0%. Foreign-born TB cases were younger (median age, 28 vs. 75 years), and had extrapulmonary TB or multidrug-TB more often than Finnish-born cases (P<0.01 for all comparisons). Foreign-born cases were born in 60 different countries; most commonly in Somalia (25.5%). Altogether 795 isolates were genotyped; 31.2% belonged to 80 different clusters (range, 2-13 cases/cluster). Fourteen (17.5%) clusters included isolates from both Finnish-born and foreign-born cases. An epidemiological link between cases was identified by (epidemiological) background information in two clusters. Although the proportion of foreign-born TB cases was considerable, our data suggests that transmission of TB between foreign and Finnish born population is uncommon.

Cross-Contamination versus Outbreak: Pre-XDR Mycobacterial Strains Confirmed by Whole-Genome Sequencing

Whole-genome sequencing (WGS) is promising for the quality control of laboratory facilities for Mycobacterium tuberculosis (MTB) strains. We describe the clinical and laboratory characteristics of false positive versus true positive MTB cultures based on WGS, which were experienced in a real clinical setting. Strain harvest and DNA extraction from seven isolates from pre-extensive drug-resistant (pre-XDR) TB patients transferred to the Korea University Ansan Hospital were performed, and epidemiologic links and clinical information, including the phenotypic drug susceptibility test (pDST), were investigated. WGS was performed using Ion GeneStudio with an ION530tm chip (average sequencing depth, ~100-fold). In the phylogenetic tree, identical and different strains were distributed separately. Five of the seven isolates were identical; the remaining two isolates differed from the others. The images of the referred pre-XDR-TB patients with false positive MTB that were analyzed were of regions close to old TB scars. Further, the results of WGS gene mutation analysis for ethambutol, streptomycin, and fluoroquinolone resistance in all six patients were not concordant with the pDST results. WGS and clinical information were useful in differentiating laboratory cross-contamination from true positive TB, thereby avoiding the unnecessary treatment of false positive patients and delay in treating true positive TB patients, with reliable genotypic drug resistance results.

The value of the continuous genotyping of multi-drug resistant tuberculosis over 20 years in Spain

Molecular epidemiology of circulating clinical isolates is crucial to improve prevention strategies. The Spanish Working Group on multidrug resistant tuberculosis (MDR-TB) is a network that monitors the MDR-TB isolates in Spain since 1998. The aim of this study was to present the study of the MDR-TB and extensively drug-resistant tuberculosis (XDR-TB) patterns in Spain using the different recommended genotyping methods over time by a national coordinated system. Based on the proposed genotyping methods in the European Union until 2018, the preservation of one method, MIRU-VNTR, applied to selected clustered strains permitted to maintain our study open for 20 years. The distribution of demographic, clinical and epidemiological characteristics of clustered and non-clustered cases of MDR/XDR tuberculosis with proportion differences as assessed by Pearson’s chi-squared or Fisher’s exact test was compared. The differences in the quantitative variables using the Student's-t test and the Mann–Whitney U test were evaluated. The results obtained showed a total of 48.4% of the cases grouped in 77 clusters. Younger age groups, having a known TB case contact (10.2% vs 4.7%) and XDR-TB (16.5% vs 1.8%) were significantly associated with clustering. The largest cluster corresponded to a Mycobacterium bovis strain mainly spread during the nineties. A total of 68.4% of the clusters detected were distributed among the different Spanish regions and six clusters involving 104 cases were grouped in 17 and 18 years. Comparison of the genotypes obtained with those European genotypes included in The European Surveillance System (TESSy) showed that 87 cases had become part of 20 European clusters. The continuity of MDR strain genotyping in time has offered a widespread picture of the situation that allows better management of this public health problem. It also shows the advantage of maintaining one genotyping method over time, which allowed the comparison between ancient, present and future samples.