Quantitative PCR for leprosy diagnosis and monitoring in household contacts: A follow-up study, 2011-2018

Role of histopathological, serological and molecular findings for the early diagnosis of treatment failure in leprosy

BACKGROUND

Treatment failure (TF) in leprosy following multidrug therapy (MDT) presents a significant challenge. The current World Health Organization (WHO) fixed-duration MDT regimen, based on lesion count, might not be adequate. Leprosy lacks clear-cut objective cure criteria, and the predictive value of post-MDT histopathological findings remains uncertain. This study aims to identify predictive factors for TF among leprosy patients who have completed the WHO-recommended MDT.

METHODS

An analysis was conducted on 80 individuals from a national leprosy reference center, comprising 40 TF cases (with a mean relapse at 13.0 months) and 40 controls (with a mean of 113.1 months without disease signs). Various epidemiological and clinical-laboratory parameters were assessed post-MDT.

RESULTS

In skin samples, the presence of foamy granuloma (OR = 7.36; 95%CI2.20-24.60; p = 0.0012) and histological bacillary index (hBI) ≥ 1+ (OR = 1.55; 95%CI1. 22-1.99; p = 0.0004) were significantly associated with TF, with odds ratios of 7.36 and 1.55, respectively. Individuals who experienced TF had a mean hBI of 3.02+ (SD ± 2.02), while the control group exhibited a mean hBI of 1.8+ (SD ± 1.88). An hBI ≥ 3 + showed a sensitivity of 73% and a specificity of 78% for TF detection (AUC: 0.75; p = 0.0001). Other histopathological features like epithelioid granulomas, and skin changes did not show significant associations (p > 0.05). Additionally, higher anti-phenolic glycolipid-I (anti-PGL-I) ELISA index (EI) levels were linked to a 1.4-fold increased likelihood for TF (OR = 1.4; 95%CI1.13-1.74; p = 0.0019). A mean EI of 4.48 (SD ± 2.80) was observed, with an EI ≥ 3.95 showing a sensitivity of 79% and a specificity of 59% for TF detection (AUC: 0.74; p = 0.0001). Moreover, the presence of Mycobacterium leprae (M. leprae) DNA in real-time polymerase chain reaction (qPCR) was associated with a 3.43-fold higher likelihood of TF. Multivariate regression analysis indicated that concurrent presentation of neural/perineural lymphocytic infiltrate, foamy granuloma, hBI ≥ 1+, and EI ≥ 1 markedly increased the likelihood of TF by up to 95.41%.

CONCLUSION

Persistence of nerve-selective lymphocytic infiltrate, foamy granulomas, and bacilli in skin biopsies, and elevated EI post-MDT, may serve as predictive factors for identifying individuals at higher probability of TF.

An update of the diagnosis, treatment, and prevention of leprosy: A narrative review

Leprosy is an infectious disease that remains a public health concern. It is caused by acid-fast Bacillus leprae, which primarily affects the skin and peripheral nerves, potentially leading to long-term disability and stigma. However, current and previous efforts have focused on developing better diagnostic and therapeutic interventions for leprosy, and its prevention needs to be addressed. In this review, we organize the currently published papers and provide updates on the global epidemiology, diagnosis, treatment, and prevention of leprosy. Several online databases, including MEDLINE (National Library of Medicine, Bethesda, MD), PubMed, EMBASE, Web of Science, and Google Scholar, were searched to collect relevant published papers. As a public health issue, the World Health Organization set the goal of leprosy elimination with a prevalence of <1 case per 10,000 people, which was achieved in 2000 and in most countries by 2010, mainly owing to the treatment of leprosy using drugs starting in 1980 and no-cost access for patients since 1995. Although diagnostic and therapeutic techniques have improved, the new occurrence of leprosy remains a critical global disease burden. With continuous technological improvements in diagnosing and treating leprosy, obtaining more relevant healthcare knowledge and preventing leprosy disability are crucial.

qPCR detection of Mycobacterium leprae DNA in urine samples of leprosy patients using the Rlep gene target

Background

Leprosy, a chronic infectious disease caused by Mycobacterium leprae, continues to pose a public health challenge in many parts of the world. Early and accurate diagnosis is crucial for effective treatment and prevention of disabilities associated with the disease. Molecular techniques such as PCR have demonstrated great potential as a diagnostic tool for directly detecting M. leprae DNA in different clinical samples, providing better sensitivity and specificity than conventional diagnostic techniques. The objective of this study was to measure the amount of M. leprae DNA in leprosy patients' urine samples using the Rlep gene target through qPCR.

Methods

Different clinical samples such as smear, blood, and urine samples were collected from leprosy patients and healthy individuals. Leprosy patients were classified by the Ridley-Jopling classification. The Ziehl-Neelsen staining method was used for the slit skin smear (SSS) samples, and the bacteriological index (BI) was calculated for leprosy patients. DNA extraction and qPCR were performed for all three types of clinical samples using the Rlep gene target.

Results

The Mycobacterial leprae DNA was successfully detected and quantified in all clinical samples across all types of leprosy among all the study groups using the Rlep gene (129 bp) target. The Rlep gene target was able to detect the presence of M. leprae DNA in 100% of urine, 96.1% of blood, and 92.2% of SSS samples of leprosy patients. Urine samples showed significant differences (p < 0.001) between the control and the different clinical forms and between borderline tuberculoid (BT) and pure neuritic leprosy (PNL) cases. There are significant differences in cycle threshold (Ct) values between control cases and clinical categories (p < 0.001), as well as specific differences within clinical categories (p < 0.001), reflecting the variability in bacterial load and detection sensitivity across different sample types and clinical manifestations of leprosy.

Conclusion

Overall, this study's findings suggest that the qPCR technique can be used to detect M. leprae DNA in urine samples of leprosy patients using the Rlep gene target. It can also be used for diagnosing the disease and monitoring the effectiveness of anti-leprosy drugs, including multi-drug therapy (MDT), across various leprosy disease groups.

Models for predicting the risk of illness in leprosy contacts in Brazil: Leprosy prediction models in Brazilian contacts

OBJECTIVE

This study aims to develop and validate predictive models that assess the risk of leprosy development among contacts, contributing to an enhanced understanding of disease occurrence in this population.

METHODS

A cohort of 600 contacts of people with leprosy treated at the National Reference Center for Leprosy and Health Dermatology at the Federal University of Uberlândia (CREDESH/HC-UFU) was followed up between 2002 and 2022. The database was divided into two parts: two-third to construct the disease risk score and one-third to validate this score. Multivariate logistic regression models were used to construct the disease score.

RESULTS

Of the four models constructed, model 3, which included the variables anti-phenolic glycolipid I immunoglobulin M positive, absence of Bacillus Calmette-Guérin vaccine scar and age ≥60 years, was considered the best for identifying a higher risk of illness, with a specificity of 89.2%, a positive predictive value of 60% and an accuracy of 78%.

CONCLUSIONS

Risk prediction models can contribute to the management of leprosy contacts and the systematisation of contact surveillance protocols.

Target product profiles: leprosy diagnostics

The World Health Organization (WHO) aims to reduce new leprosy cases by 70% by 2030, necessitating advancements in leprosy diagnostics. Here we discuss the development of two WHO's target product profiles for such diagnostics. These profiles define criteria for product use, design, performance, configuration and distribution, with a focus on accessibility and affordability. The first target product profile outlines requirements for tests to confirm diagnosis of leprosy in individuals with clinical signs and symptoms, to guide multidrug treatment initiation. The second target product profile outlines requirements for tests to detect Mycobacterium leprae or M. lepromatosis infection among asymptomatic contacts of leprosy patients, aiding prophylactic interventions and prevention. Statistical modelling was used to assess sensitivity and specificity requirements for these diagnostic tests. The paper highlights challenges in achieving high specificity, given the varying endemicity of M. leprae, and identifying target analytes with robust performance across leprosy phenotypes. We conclude that diagnostics with appropriate product design and performance characteristics are crucial for early detection and preventive intervention, advocating for the transition from leprosy management to prevention.

Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review

Leprosy is a neglected tropical disease that can cause physical injury and mental disability. Diagnosis is primarily clinical, but can be inconclusive due to the absence of initial symptoms and similarity to other dermatological diseases. Artificial intelligence (AI) techniques have been used in dermatology, assisting clinical procedures and diagnostics. In particular, AI-supported solutions have been proposed in the literature to aid in the diagnosis of leprosy, and this Systematic Literature Review (SLR) aims to characterize the state of the art. This SLR followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework and was conducted in the following databases: ACM Digital Library, IEEE Digital Library, ISI Web of Science, Scopus, and PubMed. Potentially relevant research articles were retrieved. The researchers applied criteria to select the studies, assess their quality, and perform the data extraction process. Moreover, 1659 studies were retrieved, of which 21 were included in the review after selection. Most of the studies used images of skin lesions, classical machine learning algorithms, and multi-class classification tasks to develop models to diagnose dermatological diseases. Most of the reviewed articles did not target leprosy as the study's primary objective but rather the classification of different skin diseases (among them, leprosy). Although AI-supported leprosy diagnosis is constantly evolving, research in this area is still in its early stage, then studies are required to make AI solutions mature enough to be transformed into clinical practice. Expanding research efforts on leprosy diagnosis, coupled with the advocacy of open science in leveraging AI for diagnostic support, can yield robust and influential outcomes.

Systematic Review of Survival Analysis in Leprosy Studies-Including the Following Outcomes: Relapse, Impairment of Nerve Function, Reactions and Physical Disability

Leprosy is a public health problem in South American, African and Oceanian countries. National programs need to be evaluated, and the survival analysis model can aid in the construction of new indicators. The aim of this study was to assess the period of time until the outcomes of interest for patients with or exposed to leprosy by means of survival analysis surveys. This review researched articles using the databases of PubMed, Science Direct, Scopus, Scielo and BVS published in English and Portuguese. Twenty-eight articles from Brazil, India, Bangladesh, the Philippines and Indonesia were included. The Kaplan-Meier method, which derives the log-rank test, and Cox's proportional hazards regression, which obtains the hazard ratio, were applied. The mean follow-up until the following outcomes were: (I) leprosy (2.3 years) in the population who were exposed to it, (II) relapse (5.9 years), (III) clinical manifestations before, during and after treatment-nerve function impairment (5.2 years), leprosy reactions (4.9 years) and physical disability (8.3 years) in the population of patients with leprosy. Therefore, the use of survival analysis will enable the evaluation of national leprosy programs and assist in the decision-making process to face public health problems.

Bacilloscopy and polymerase chain reaction of slit-skin smears and anti-phenolic glycolipid-I serology for Hansen's disease diagnosis

The bacilloscopy of the slit-skin smear (SSS) is the exclusive laboratory test associated with dermato-neurological evaluation for Hansen's disease (HD) diagnosis; however, it is negative in the majority of PB or primary neural forms. Thus, a PCR technique involving different sequences and target genes has been performed with an aim to increase the sensitivity and specificity of M. leprae identification, especially in patients with low bacillary loads. Additionally, serological assays based on antibody response reflect infection levels and indicate that this could be a simpler, less invasive technique for estimating M. leprae exposure. Serological tests and PCR have been shown to be more sensitive and accurate than the SSS. Our study aimed to measure accuracy and performance among the SSS and PCR of dermal scrapings stored on filter paper and APGL-I serology for diagnosis in HD. A cross-sectional study analyzing the medical records (n = 345) of an HD outpatient-dermatology clinic from 2014 to 2021 was conducted. Accuracy performance parameters, correlation, and concordance were used to assess the value among the SSS, PCR, and APGL-I exams in HD. The SSS presented 24.5% sensitivity, 100% specificity, 37.4% accuracy, and the lowest negative predictive value (21.5%). The PCR assay had 41, 100, and 51% sensitivity, specificity, and accuracy, respectively. PCR and APGL-I serology increased the detection of HD cases by 16 and 20.6%, respectively. PCR was positive in 51.3% of patients when the SSS was negative. The SSS obtained moderate concordance with PCR [k-value: 0.43 (CI: 0.33-0.55)] and APGL-I [k-value: 0.41 (CI: 0.31-0.53)]. A moderate positive correlation was found between the APGL-I index and the bacillary index (r = 0.53; P < 0.0001). Thus, the use of the SSS is a low sensitivity and accuracy method due to its low performance in HD detection. The use of PCR and serological tests allows for a more sensitive and accurate diagnosis of patients.

Advances in the Diagnosis of Leprosy

Leprosy is a public health issue, and early detection is critical to avert disability. Despite the global attempt to eradicate this disease as a public health problem, it remains an important cause of global neurological disability. India, Brazil and Indonesia share more than 70% of the cases. The reduction of new cases is a priority in the WHO global strategy 2021-2030 which aims to reduce disease transmission in the community by diagnosing cases and identifying subclinical infection. The clinical manifestations of leprosy range from a few to several lesions. The identification remains difficult due to the limited sensitivity of traditional approaches based on bacillary counts of skin smears and histology. To aid in the diagnosis of this disease, molecular biology, and biotechnological technologies have been applied, each with its own set of benefits and downsides despite providing an essential tool to validate the clinical diagnosis of leprosy. Because of this, it is strongly recognized that specific, inexpensive point of care technologies should be developed, particularly to identify asymptomatic M. leprae infections or leprosy nearer to the suspected cases seeking medical attention. Thus, this review will provide an overview of the advancements in leprosy diagnosis over the world. The purpose of this review is to improve our understanding of the outcomes of current tests and technologies used in leprosy diagnosis and to emphasize critical aspects concerning the detection of leprosy bacilli.

Factors associated with the development of leprosy in Brazilian contacts: a systematic review

People who interact with leprosy patients in their environment, neighborhood, family, or social relationships are at risk to develop the disease. This systematic review investigated the risk and protective factors associated with the development of leprosy in Brazilian contacts. The studies were found in Cochrane Library, PubMed (MEDLINE), Embase, Virtual Health Library, grey literature and hand search until July 2021. The study selection, data extraction and quality assessment were independently performed by two investigators. The quality assessment was performed using the Newcastle-Ottawa Scale (NOS). This review was registered in PROSPERO (CRD42020160680). Seventeen articles fulfilled the inclusion criteria (n=544). The immunological and molecular factors, such as Anti-phenolic Glycolipid Antibodies (Anti-PGL-1) seropositivity, negative Mitsuda test, absence of Bacillus Calmette-Guérin (BCG) scar, positive Polymerase Chain Reaction (PCR) in blood; age and race; conviviality, education, contact time and type of contact, as well as elements related to the index case (bacilloscopic index; genetic conditions, family relationships), and some combined factors were shown to be relevant risk factors associated with the development of the disease in Brazilian leprosy contacts. The protective factors reported were the presence of one or more BCG scars, positive Mitsuda test, and education level. All selected studies were considered of high quality according to NOS. The knowledge of disease-related risk and protective factors provides the scientific basis for decision-making in the management of the disease in leprosy contacts.

A comparison of three types of targeted, community-based methods aimed at promoting early detection of new leprosy cases in rural parts of three endemic states in India

Background

India achieved elimination of leprosy nationally in 2005, but since then the number of patients with grade 2 disability at diagnosis increased steadily indicating delay in diagnosis. Therefore, there was a need for public health interventions which can increase case finding in their earlier stage. The objective of this study is to compare the effectiveness of three such community-based interventions; 1) Enhancement of community awareness on leprosy; 2) Education and motivation of “Index” leprosy cases; and 3) Involvement of Non-Formal Health Practitioners (NFHPs) to promote early detection of new cases of leprosy.

Methodology/principal findings

Three community-based interventions were implemented between April 2016 and March 2018, embedded within the National Leprosy Eradication Program (NLEP) of India. Interventions were 1) increasing awareness through involvement of Gram Panchayat (local government) in the community regarding early signs of leprosy (Awareness), 2) providing health education and motivating newly diagnosed leprosy patients to bring suspects from their contacts (Index) and 3) training local non-formal health practitioners (NFHP). Each intervention was implemented in a group of ten blocks (sub-division of district) with an additional ten blocks as control (with no intervention). The main outcomes were number of new cases detected and number of grade 2 disability among them. They were obtained from the routine NLEP information system and compared between these interventions. On an average, there was an addition of 1.98 new cases in Awareness blocks, 1.13 in NFHP blocks and 1.16 cases in Index intervention blocks per month per block after adjusting for changes in control blocks during the same period. In terms of ratio, there was a 61%, 40% and 41% increase in case notification in awareness, Index and NFHP intervention, respectively. Overall, the percentage of grade 2 disability across intervention blocks declined.

Conclusion

The Awareness intervention appears to be more effective in detection of new cases, compared to Index case motivation and sensitization of NFHPs. However, it is important to stress that while selecting strategies to increase early diagnosis it is important to determine, which is the most appropriate for each context or area and must be decided depending on the local context.

RLEP LAMP for the laboratory confirmation of leprosy: towards a point-of-care test

BACKGROUND

Nucleic acid-based amplification tests (NAAT), above all (q)PCR, have been applied for the detection of Mycobacterium leprae in leprosy cases and household contacts with subclinical infection. However, their application in the field poses a range of technical challenges. Loop-mediated isothermal amplification (LAMP), as a promising point-of-care NAAT does not require sophisticated laboratory equipment, is easy to perform, and is applicable for decentralized diagnosis at the primary health care level. Among a range of gene targets, the M. leprae specific repetitive element RLEP is regarded as highly sensitive and specific for diagnostic applications.  METHODS: Our group developed and validated a dry-reagent-based (DRB) RLEP LAMP, provided product specifications for customization of a ready-to-use kit (intended for commercial production) and compared it against the in-house prototype. The assays were optimized for application on a Genie® III portable fluorometer. For technical validation, 40 "must not detect RLEP" samples derived from RLEP qPCR negative exposed and non-exposed individuals, as well as from patients with other conditions and a set of closely related mycobacterial cultures, were tested together with 25 "must detect RLEP" samples derived from qPCR confirmed leprosy patients. For clinical validation, 150 RLEP qPCR tested samples were analyzed, consisting of the following categories: high-positive samples of multibacillary (MB) leprosy patients (> 10.000 bacilli/extract), medium-positive samples of MB leprosy patients (1.001-10.000 bacilli/extract), low-positive samples of MB leprosy patients (1-1.000 bacilli/extract), endemic controls and healthy non-exposed controls; each n = 30.  RESULTS: Technical validation: both LAMP formats had a limit of detection of 1.000 RLEP copies, i.e. 43-27 bacilli, a sensitivity of 92% (in-house protocol)/100% (ready-to-use protocol) and a specificity of 100%. Reagents were stable for at least 1 year at 22 °C. Clinical validation: Both formats showed a negativity rate of 100% and a positivity rate of 100% for high-positive samples and 93-100% for medium positive samples, together with a positive predictive value of 100% and semi-quantitative results. The positivity rate for low-positive samples was 77% (in-house protocol)/43% (ready-to-use protocol) and differed significantly between both formats.  CONCLUSIONS: The ready-to-use RLEP DRB LAMP assay constitutes an ASSURED test ready for field-based evaluation trials aiming for routine diagnosis of leprosy at the primary health care level.

A new paradigm for leprosy diagnosis based on host gene expression

Transcriptional profiling is a powerful tool to investigate and detect human diseases. In this study, we used bulk RNA-sequencing (RNA-Seq) to compare the transcriptomes in skin lesions of leprosy patients or controls affected by other dermal conditions such as granuloma annulare, a confounder for paucibacillary leprosy. We identified five genes capable of accurately distinguishing multibacillary and paucibacillary leprosy from other skin conditions. Indoleamine 2,3-dioxygenase 1 (IDO1) expression alone was highly discriminatory, followed by TLR10, BLK, CD38, and SLAMF7, whereas the HS3ST2 and CD40LG mRNA separated multi- and paucibacillary leprosy. Finally, from the main differentially expressed genes (DEG) and enriched pathways, we conclude that paucibacillary disease is characterized by epithelioid transformation and granuloma formation, with an exacerbated cellular immune response, while multibacillary leprosy features epithelial-mesenchymal transition with phagocytic and lipid biogenesis patterns in the skin. These findings will help catalyze the development of better diagnostic tools and potential host-based therapeutic interventions. Finally, our data may help elucidate host-pathogen interplay driving disease clinical manifestations.

Blood RNA signature RISK4LEP predicts leprosy years before clinical onset

BACKGROUND

Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection.

METHODS

We investigated differential gene expression (DGE) by RNA-Seq between progressors before presence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR).

FINDINGS

Although no significant intra-individual longitudinal variation within leprosy progressors was identified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identified a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted in a final 4-gene signature, designated RISK4LEP (MT-ND2, REX1BD, TPGS1, UBC) (AUC=86.4%).

INTERPRETATION

This study identifies for the first time a prospective transcriptional risk signature in blood predicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in contacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development.

FUNDING

This study was supported by R2STOP Research grant, the Order of Malta-Grants-for-Leprosy-Research, the Q.M. Gastmann-Wichers Foundation and the Leprosy Research Initiative (LRI) together with the Turing Foundation (ILEP# 702.02.73 and # 703.15.07).

Insights into Mycobacterium leprae Proteomics and Biomarkers-An Overview

Although leprosy is curable, the identification of biomarkers for the early diagnosis of leprosy would play a pivotal role in reducing transmission and the overall prevalence of the disease. Leprosy-specific biomarkers for diagnosis, particularly for the paucibacillary disease, are not well defined. Therefore, the identification of new biomarkers for leprosy is one of the prime themes of leprosy research. Studying Mycobacterium leprae, the causative agent of leprosy, at the proteomic level may facilitate the identification, quantification, and characterization of proteins that could be potential diagnostics or targets for drugs and can help in better understanding the pathogenesis. This review aims to shed light on the knowledge gained to understand leprosy or its pathogen employing proteomics and its role in diagnosis.

Leprosy incidence and risk estimates in a 33-year contact cohort of leprosy patients

Reduction in incidence has been associated with the introduction of novel approaches, like chemo/immune-prophylaxis. Incidence determined through follow-up cohort studies can evaluate the implementation of these innovative policies towards control and prevention. We have assessed the incidence in our contacts cohort over past 33 years, considering the effect of demographic and clinical variables. Survival analysis was used to estimate the risk of leprosy. A total of 9024 contacts were evaluated, of which 192 developed leprosy, resulting in an overall incidence of 1.4/1000 person-years. The multivariate analysis showed that the major risk factors were (i) contact from MB index cases and (ii) consanguinity (iii) intra household contact. Lower risk was detected for contacts with BCG scar who were revaccinated. There was a significant decrease in accumulated risk between the 2011-2019 period compared with 1987, probably linked to the improvement in laboratory tools to monitor contacts, thereby providing early diagnosis of contacts at intake and reduction of transmission. Our findings suggest that a combination of contact surveillance and tracing, adequate neurodermatological examination, and availability of molecular tools is highly effective in supporting early diagnosis, while a second dose of the BCG vaccination can exert extra protection.

Genomic Characterization of Mycobacterium leprae to Explore Transmission Patterns Identifies New Subtype in Bangladesh

Mycobacterium leprae, the causative agent of leprosy, is an unculturable bacterium with a considerably reduced genome (3.27 Mb) compared to homologues mycobacteria from the same ancestry. In 2001, the genome of M. leprae was first described and subsequently four genotypes (1-4) and 16 subtypes (A-P) were identified providing means to study global transmission patterns for leprosy. In order to understand the role of asymptomatic carriers we investigated M. leprae carriage as well as infection in leprosy patients (n = 60) and healthy household contacts (HHC; n = 250) from Bangladesh using molecular detection of the bacterial element RLEP in nasal swabs (NS) and slit skin smears (SSS). In parallel, to study M. leprae genotype distribution in Bangladesh we explored strain diversity by whole genome sequencing (WGS) and Sanger sequencing. In the studied cohort in Bangladesh, M. leprae DNA was detected in 33.3% of NS and 22.2% of SSS of patients with bacillary index of 0 whilst in HHC 18.0% of NS and 12.3% of SSS were positive. The majority of the M. leprae strains detected in this study belonged to genotype 1D (55%), followed by 1A (31%). Importantly, WGS allowed the identification of a new M. leprae genotype, designated 1B-Bangladesh (14%), which clustered separately between the 1A and 1B strains. Moreover, we established that the genotype previously designated 1C, is not an independent subtype but clusters within the 1D genotype. Intraindividual differences were present between the M. leprae strains obtained including mutations in hypermutated genes, suggesting mixed colonization/infection or in-host evolution. In summary, we observed that M. leprae is present in asymptomatic contacts of leprosy patients fueling the concept that these individuals contribute to the current intensity of transmission. Our data therefore emphasize the importance of sensitive and specific tools allowing post-exposure prophylaxis targeted at M. leprae-infected or -colonized individuals.

Ultra-sensitive detection of Mycobacterium leprae: DNA extraction and PCR assays

Leprosy urgently needs a precise and early diagnostic tool. The sensitivity of the direct (bacilli staining, Mycobacterium leprae DNA) and indirect (antibody levels, T cell assays) diagnostics methods vary based on the clinical form. Recently, PCR-based M. leprae DNA detection has been shown to differentially diagnose leprosy from other dermatological conditions. However, accuracy can still be improved, especially for use with less invasive clinical samples. We tested different commercial DNA extraction kits: DNeasy Blood & Tissue, QIAamp DNA Microbiome, Maxwell 16 DNA Purification, PowerSoil DNA Isolation; as well as in-house phenol-chloroform and Trizol/FastPrep methods. Extraction was performed on M. leprae-infected mouse footpads and different clinical samples of leprosy patients (skin biopsies and scrapings, lesion, oral and nasal swabs, body hair, blood on FTA cards, peripheral whole blood). We observed that the Microbiome kit was able to enrich for mycobacterial DNA, most likely due the enzymatic digestion cocktail along with mechanical disruption involved in this method. Consequently, we had a significant increase in sensitivity in skin biopsies from paucibacillary leprosy patients using a duplex qPCR targeting 16S rRNA (M. leprae) and 18S rRNA (mammal) in the StepOnePlus system. Our data showed that the presence of M. leprae DNA was best detected in skin biopsies and skin scrapings, independent of the extraction method or the clinical form. For multibacillary patients, detection of M. leprae DNA in nasal swabs indicates the possibility of having a much less invasive sample that can be used for the purposes of DNA sequencing for relapse analysis and drug resistance monitoring. Overall, DNA extracted with the Microbiome kit presented the best bacilli detection rate for paucibacillary cases, indicating that investments in extraction methods with mechanical and DNA digestion should be made.