Occurrence and Nature of Double Alleles in Variable-Number Tandem-Repeat Patterns of More than 8,000 Mycobacterium tuberculosis Complex Isolates in The Netherlands

Insights into the Complexity of a Dormant Mycobacterium tuberculosis Cluster Once Transmission Is Resumed

Genotyping tools help identify the complexity in Mycobacterium tuberculosis transmission clusters. We carried out a thorough analysis of the epidemiological and bacteriological complexity of a cluster in Almería, Spain. The cluster, initially associated with Moroccan migrants and with no secondary cases identified in 4 years, then reappeared in Spanish-born individuals. In one case, two Mycobacterium tuberculosis clonal variants were identified. We reanalyzed the cluster, supported by the characterization of multiple cultured isolates and respiratory specimens, whole-genome sequencing, and epidemiological case interviews. Our findings showed that the cluster, which was initially thought to have restarted activity with just a single case harboring a small degree of within-host diversity, was in fact currently growing due to coincidental reactivation of past exposures, with clonal diversity transmitted throughout the cluster. In one case, within-host diversity was amplified, probably due to prolonged diagnostic delay. IMPORTANCE The precise study of the dynamics of tuberculosis transmission in socio-epidemiologically complex scenarios may require more thorough analysis than the standard molecular epidemiology strategies. Our study illustrates the epidemiological and bacteriological complexity present in a transmission cluster in a challenging epidemiological setting with a high proportion of migrant cases. The combination of whole-genome sequencing, refined and refocused epidemiological interviews, and in-depth analysis of the bacterial composition of sputa and cultured isolates was crucial in order to correctly reinterpret the true nature of this cluster. Our global approach allowed us to reinterpret correctly the unnoticed epidemiological and bacteriological complexity involved in the Mycobacterium tuberculosis transmission event under study, which had been overlooked by the usual molecular epidemiology approaches.

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.

Genotypic diversity of Mycobacterium tuberculosis isolates from North-Central Indian population

BACKGROUND

Different strains of Mycobacterium tuberculosis (MTB) are known to have different epidemiological and clinical characteristics. Some of them are widely distributed and associated with drug resistance, whereas others are locally predominated. Molecular epidemiological investigations have always been beneficial in identifying new strains and studying their transmission dynamics. Sahariya a primitive tribe of North Madhya Pradesh, India, has already been reported to have high prevalence of tuberculosis (TB) than their non-tribal neighbours. However, the information about MTB genotypes prevalent in Sahariya tribe and their non-tribal neighbours is not available.

METHODS

A total of 214 clinical isolates representing Sahariya tribe and non-tribes were analyzed by spoligotyping and MIRU-VNTR typing.

RESULTS

The EAI3_IND/SIT11 genotype was observed as major genotype in Sahariya tribe followed by CAS1_Delhi/SIT26 genotype. A 3.04 fold higher risk of getting TB with EAI3_IND/SIT11 genotype was observed in Sahariya as compared to the non-tribal population. The EAI_IND/SIT11 genotype also found to have more number of MDR-TB cases in Sahariya as well as true and possible transmission links. In Sahariya tribe, 3 clusters (6 isolates) reflected true transmission links, whereas 8 clusters consisted of 26 isolates revealed possible transmission links within the same geographical location or nearby houses.

CONCLUSION

The present study highlighted the predominance of EAI3_IND/SIT11 genotype in Sahariya tribe followed by CAS1_Delhi/SIT26 genotype. Combined approach of MIRU-VNTR typing and spoligotyping was observed more favourable in discrimination of MTB genotypes. Further, longitudinal studies using whole genome sequencing can provide more insights into genetic diversity, drug resistance and transmission dynamics of these prevalent genotypes.

Mixed Mycobacterium tuberculosis-Strain Infections Are Associated With Poor Treatment Outcomes Among Patients With Newly Diagnosed Tuberculosis, Independent of Pretreatment Heteroresistance

Background

Heteroresistant Mycobacterium tuberculosis infections (defined as concomitant infection with drug-resistant and drug-susceptible strains) may explain the higher risk of poor tuberculosis treatment outcomes observed among patients with mixed-strain M. tuberculosis infections. We investigated the clinical effect of mixed-strain infections while controlling for pretreatment heteroresistance in a population-based sample of patients with tuberculosis starting first-line tuberculosis therapy in Botswana.

Methods

We performed 24-locus mycobacterial interspersed repetitive unit-variable number tandem-repeat analysis and targeted deep sequencing on baseline primary cultured isolates to detect mixed infections and heteroresistance, respectively. Drug-sensitive, micro-heteroresistant, macro-heteroresistant, and fixed-resistant infections were defined as infections in which the frequency of resistance was <0.1%, 0.1%-4%, 5%-94%, and ≥95%, respectively, in resistance-conferring domains of the inhA promoter, the katG gene, and the rpoB gene.

Results

Of the 260 patients with tuberculosis included in the study, 25 (9.6%) had mixed infections and 30 (11.5%) had poor treatment outcomes. Micro-heteroresistance, macro-heteroresistance, and fixed resistance were found among 11 (4.2%), 2 (0.8%), and 11 (4.2%), respectively, for isoniazid and 21 (8.1%), 0 (0%), and 10 (3.8%), respectively, for rifampicin. In multivariable analysis, mixed infections but not heteroresistant infections independently predicted poor treatment outcomes.

Conclusions

Among patients starting first-line tuberculosis therapy in Botswana, mixed infections were associated with poor tuberculosis treatment outcomes, independent of heteroresistance.

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

Background

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

Implementation

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

Validation

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

Results

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

Conclusion

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