Genetic diversity of Mycobacterium leprae: Need to move towards genome-wide approaches

Introduction

Leprosy is an infectious dermato-neurological disease that affects the peripheral nerves, the mucosal surfaces of the upper respiratory tract and skin1. Mycobacterium leprae and Mycobacterium lepromatosis have been identified as causal agents of leprosy2. Globally, in the last decade, over 200,000 new cases of leprosy were documented each year, except during the COVID-19 pandemic time. India, Brazil and Indonesia together contributed to >75 per cent of the global caseload3. A high number of new leprosy cases are still found in the pockets of hyperendemic regions of India4 while the annual new case detection rate in the country has also remained almost stagnant (0.5-0.6/10,000) during the last decade5.

The perpetual presence of leprosy is believed to be the result of human-to-human transmission67 and extended close contact with a leprosy patient is a major risk factor. The relative risk of leprosy is increased by eight to 10-fold among the contacts of multibacillary and two to four-fold among the contacts of paucibacillary patients8910. Some animal species have been described as reservoir hosts of M. leprae such as nine-banded armadillos, red squirrels and chimpanzees111213.

Molecular epidemiological studies leading to the discovery of prevalent strains in a certain geographical area have played a crucial role in improving the understanding of transmission of pathogens1415. Whole-genome sequencing (WGS) of nearly 300 genomes of M. leprae has been done and revealed some phylogeographically associated single-nucleotide polymorphisms (SNPs) that have been used in the classification of the strains of M. leprae into four genotypes (1 to 4) and 16 subtypes (A to P)16. Among these, the subtype 1D has been reported as the most prevalent genotype in India1718.

To date, the knowledge about polymorphic markers to investigate their genetic diversity and their transmission in Indian context has been scarce, and WGS is yet to be deployed in molecular epidemiology study. To the best of our knowledge, only four M. leprae genomes have been reported from India, which indicates that further efforts are required in this area to adequately understand the level of genetic diversity of Indian M. leprae strains13. This review narrates the progression of molecular epidemiology of leprosy and the contribution of WGS-derived information in facilitating the discovery of the genomic markers and mutations related to drug resistance and genotyping in the Indian context.

Whole-genome sequencing

The ability to sequence the entire genome of M. leprae directly from clinical specimens has been a major breakthrough, especially because M. leprae has remained uncultivable since its discovery in 19731920. The WGS of M. leprae TN strain completed in 2001 revealed that it has genome size of 3,268,203 bp, 1604 encoded proteins and 1116 pseudogenes. M. leprae lacks the machinery to survive without a host owing to its drastic reductive evolution2122. In addition, the identification of three informative SNPs at positions 14676, 1642875 and 2935685 in M. leprae strains from 21 countries established a genotyping system classifying M. leprae into four genotypes, namely SNP type 1 to 41623. Comparative genomic analysis of the M. leprae Br4923 strain with the M. leprae TN strain revealed that its genome is 141 bp smaller. Subsequently, it also allowed M. leprae to be classified into 16 SNP subtypes. Based on the presence of the SNPs, these subtypes are referred to as A to P (where M. leprae TN belongs to subtype 1A and the strain M. leprae Br4923 belongs to subtype 4P)24 (Table I).

The WGS of M. leprae directly from clinical specimens was a significant step forward in interpreting the molecular epidemiology of the disease, its diagnosis, treatment and control25. Over the years, several refinements in the annotation of the M. leprae genome have been made as other mycobacterial genomes became available for comparative genomic analysis. Currently, M. leprae genome annotation reveals 2851 genes and 591 pseudogenes. As of September 2022, WGS data on 289 genomes from 43 countries were made publicly available13 (Fig. 1). Among them, sequence of only four strains were sequenced from Indian leprosy patients.

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Fig. 1

Phylogenetic tree representing Mycobacterium leprae 289^# genomes using iTOL software and the Maximum Parsimony method. The tree consists of genomes from various parts of the world where Indian genomes (n=4) are shown in red. The yellow clade represents the SNP genotype 1, the blue clade represents SNP genotype 2, the purple clade represents SNP genotype 3 and the green clade represents SNP genotype 4. ^#286 genomes previously published in a study by Hocking et al13 in 2021 and datasets of additional three genomes were obtained from NCBI and included in the combined comparison after assembly and SNP identification.

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The identification of M. lepromatosis in 2008 as another causative pathogen of leprosy was a notable discovery in leprosy research262728. The comparison of M. leprae and M. lepromatosis whole-genome sequences revealed that their ancestors had undergone a reductive evolution process together approximately 20 million yr ago. After a massive pseudogenization event, the divergence time between M. leprae and M. lepromatosis has been estimated to be approximately 13.9 million yr28. Moreover, the genome information about M. lepromatosis also helped to discover its limited geographical presence as well as its surprising association with red squirrels in Scotland2930. So far, M. lepromatosis has been detected in 1281 patient specimens. Comparative genomics revealed the presence of hemN gene in M. lepromatosis, which was missing in M. leprae and was as an element recommended for differentiating M. leprae from M. lepromatosis. Subsequently, it was observed that HemN in mycobacteria was incorrectly annotated and belongs to the radical SAM family heme chaperone HemW31.

Development & refinement of genotyping scheme

Whole-genome-based investigation allows researchers to investigate genetic variations in M. leprae such as SNPs, copy number variations and significant structural alterations in DNA. Next-generation sequencing can help us determine the genomic markers in a comprehensive manner at a single-nucleotide level that led to the development of genotyping schemes. There are several genomic regions that together contribute to genetic diversity, drug resistance and evolution; thus, a genome-wide analysis may provide a more accurate representation of evolutionary relatedness between different strains (phylogeny) and provide insight into the functional effects of genotypes of M. leprae.

Strains of M. leprae obtained from around the world are clonal and diverged by only a few SNPs, variable-number tandem repeats (VNTRs) or Short Tandem Repeats (STRs)163233. By 2009, 78 informative SNPs (defined as useful for SNP genotyping from different parts of the world) and six single-base insertions/deletions (Indels) with four informative homopolymer tracts were used to determine the SNP genotyping16. Subsequently, a more detailed genome-wide analysis of different genotypes revealed that some previously classified subtypes are better placed under a different genotype category; for example, 1C is regrouped within the genotype 1D, and 3J is placed within 3K. In addition, some genotypes have been further subdivided, such as 3K into 3K-0, 3K-1 and 3I into 3I-1 and 3I-224.

Based on phylogenetic study of 16 whole-genomes of present and ancient M. leprae strains, the 3K subtype has been considered as the most ancestral genotype34. The distribution of the 3K subtype suggests that the ancestral strain of M. leprae originated in far east Asia, although an in-depth investigation of under-explored central Asia would provide a better insight25. A study of the 290 isolates assessed for SNP analysis in China has identified the majority as subtype 3K (n=278, 95.8%) followed by subtype 1D (n=10, 3.4%) and a novel subtype 3J (n=1, 0.34%)33. However, it is important here to note that the genotype 3J, first identified in a comparative genomics study in 200916 has been phylogenomically reclassified as 3K-0 and is now considered to be part of the 3K genotype25. SNPs and Indels are also used to differentiate 3I genotype from all other genotypes (Fig. 2). Further, the investigation led to the subdivision of type 3I into types 3I-1 and 3I-2, which was based on SNP152705624 (Table II).

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Fig. 2

Identification of Mycobacterium leprae strains belonging to SNP type 3I using SNP7614 and Indel_17915: SNP type 3I uniquely exhibits a ‘T’ at position 7614 and a single copy of ‘TTGGTGGTGTA’ at position 17915 whereas all other genotypes display a ‘C’ and two copies of the ‘TTGGTGGTGTA’.

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A similar application of the comparative genomics of 24 strains belonging to SNP subtype 1D led to the identification of two subtypes that further resolved this genotype into 1D-1 and 1D-2. The 1D-1 was found to be phylogeographically associated with Venezuela (Table II)35. Subsequently, a new M. leprae genotype described as 1B-Bangladesh was identified, which clusters between the 1A and 1B strains independently. The investigation demonstrated that the genotype, previously known as 1C, clusters within the 1D genotype and is not an independent genotype36. Subsequently, a novel subtype named 3Q in skeletal samples (9^th to 11^th century) has been identified from Belarus37.

M. leprae subtypes such as 1B, 2G, 3M, 3J, 4O, 4P and the recently identified 4N/O, 1B-Bangladesh and 1D-Malagasy presented limited geographic distribution and possess characteristics phylogeographic markers which could be useful for establishing transmission links to other areas connected by migration patterns. These continuous developments in the genotyping schemes helped researchers to have a better comprehension of M. leprae evolution, as shown in Table III and Figure 3. Therefore, for better understanding and identification of specific geographically associated genotypes, the inclusion of more whole-genome sequences from Eurasia, particularly the middle east and India, is required.

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Fig. 3

A timeline of notable events in the history of the Mycobacterium leprae genotyping scheme.

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Identification of new drug resistance genes

Similar to other bacterial pathogens, M. leprae strains also experience selection pressure due to the use of anti-leprosy drugs. Selection pressure in the presence of drugs could be the driving force for emergence of drug-resistant strains that are based on mutations in rpoB (rifampicin), folP1 (dapsone) and gyrA (ofloxacin) genes. In addition, WGS comparisons have uncovered other potential candidate genes such as ribD, pks4, nth, ethA and fadD9, which might contribute to the emergence of drug resistance. The mutations identified in the ribD gene of M. leprae are linked with resistance to vadrine, a para-aminosalicylic acid drug, which was a medication used to treat leprosy in the pre-MDT era44. Such observations, made possible by WGS studies, suggest that these ribD mutations had arisen during vadrine therapy well before MDT (around 1950-1960s). Isolates, with nonsense mutations in their nth gene (involved in DNA repair), have been reported to exhibit increased sequence diversity as well as drug resistance mutations. Three newly discovered non-synonymous mutations found in the gyrB gene have been identified as infrequent and their clinical significance and distribution need systematic assessment.

Molecular epidemiology of leprosy in India

The genotyping of a wide panel of M. leprae strains from around the world has revealed strong regional connections correlating well with the human migration events leading to clonal dissemination of leprosy. For example, the European lineage (3I) reached the Americas through colonization16. However, the existing genotyping schemes have limited utility for providing the required differentiation/resolution for majority of the Indian strains. It is therefore important to carry out a detailed genome-wide analysis of M. leprae strains from various endemic regions in India to further differentiate strains from the country. Only four M. leprae genomes from India have been described so far while the raw data of 11 strains have been submitted to NCBI, but those datasets did not provide sufficient coverage for analysis39.

Previous SNP typing investigations through Sanger sequencing of M. leprae from India demonstrated that SNP subtype 1D is the most prevalent subtype (accounting for almost 76% of all cases), while other SNP types (1B, 2E, 2H and 2G) contribute a smaller fraction183845 (Table IV). Since, a majority of Indian strains are classified 1D only and not differentiated further by the existing genotyping scheme. Therefore, genome-wide comparisons of Indian strains has a potential to reveal new variable positions which may allow further differentiation.This may be useful for improving the current typing scheme. For example, the M. leprae MRHRU-235-G genome (NCBI Accession No. NZ_CP029543) is the most recent one from India submitted in the database, but no information about its genotype or SNPs were available. We analyzed this and determined its SNPs and SNP genotype as per Monot et al16 2009. It indicates a combination of SNP at position/coordinates 1642879, 2935693 and 14676 as G, A and C, respectively, which is a characteristic of SNP type-1. Similarly, a combination of SNP at positions 8453, 313361 and 61425 as C, G and G is characteristic of SNP-type-1D. Thus, genotyping and phylogenetic analysis of MRHRU-235-G revealed it to be genotype 1D (Fig. 1 and Table V) based on the comparison at the known locations of SNPs that distinguish between the strains 1A (M. leprae TN) and 1D (M. leprae MRHRU-235-G and Airaku-3 strains). Therefore, the existing PCR-genotyping scheme has a limited utility for providing further resolution.

Discussion

Today, genome analysis has a lot of potential for improving healthcare in a variety of fields, including identification of novel mutations of drug resistance, of disease progression, for enhanced diagnosis and personalized medicine. One of the challenges related to leprosy research in India is the lack of genotype information and their clinical correlation with disease severity and clinical presentations. The construction of predictive models based on WGS data aids in the classification of individuals into different risk groups, allowing for development of preventive measures and personalized therapies. Although genome sequencing technology has become more accessible owing to decreasing costs and increased throughput, yet there is a requirement to develop new strategies to enrich M. leprae DNA from clinical samples for better genome coverage. This remains a major challenge as the enrichment procedure often requires expensive kits containing custom synthesized oligo arrays34 or in-solution hybridization baits46. The expensive and commercial unavailability of custom enrichment methods for genome-wide capture of M. leprae DNA is one of the prime reasons behind non-availability of WGS-based studies for molecular epidemiology of leprosy from India.

Molecular genotyping is a vital tool for keeping a track of the type of strains prevalent in a region and also helps in differentiation between relapse and reinfection cases and for identifying mixed infections. Moreover, WGS offers an efficient approach with targeted sequencing leading to the discovery of strain-specific markers by in-depth genome analysis47. Identification of novel genomic markers might eventually aid in targeted screening by PCR-based assays and as such lowering the costs and turnaround time. Therefore, the use of WGS for a representative number of strains, followed by targeted sequencing of chosen VNTR and SNP markers using conventional PCR sequencing or PCR-RFLP methods484950 might be helpful in rapid identification of M. leprae genotype(s)13253651 especially in endemic countries such as India52.

Benefits of WGS have been immense in various spheres of M. leprae genomics and to uncover useful clues into the biology and pathogenesis of leprosy bacilli including the evolution and emergence of drug resistance. Several new genes are associated with resistance to antibiotics. One of the direct advantages of successful M. leprae genotyping is that it makes reconstructing historical human migration patterns possible. Furthermore, in many areas where leprosy is endemic such as southeast Asia and South American countries, the newly identified polymorphic markers can be relevant for molecular epidemiological investigations3653. Therefore, efforts to develop practical and affordable methods for WGS of Indian strains are needed.