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DNA Fingerprinting of Mycobacterium leprae Strains Using Variable Number Tandem Repeat (VNTR) - Fragment Length Analysis (FLA)
Published on: July 15, 2011
Real-Time PCR-Based Detection of Mycobacterium leprae From Multiple Clinical Samples for Molecular Diagnosis of
Bahou Roger Dehe1, Aby Christiane Amon2, Ouemela Venance Ban3
1UFR Marine Sciences, Laboratory of Oceanographic and Marine Resources, San Pedro University, San Pedro, Ivory Coast.
Background:
Leprosy remains endemic in Côte d'Ivoire, with persistent Grade 2 disability cases indicating ongoing challenges in early diagnosis. Classical diagnosis relies on clinical examination and microscopy, which lacks sensitivity because Mycobacterium leprae cannot be cultured. In the context of the WHO "Zero Leprosy" strategy (2021-2030), molecular tools are needed to confirm cases, detect subclinical infections, and monitor transmission.
Methods:
We developed and evaluated a real-time PCR protocol targeting the M. leprae 16S rRNA gene for molecular diagnosis. Clinical specimens (slit-skin smears and nasal mucus) were collected from 20 clinically diagnosed leprosy patients in Côte d'Ivoire. DNA/RNA extraction was performed using both a semiautomated kit (NucliSENS) and a manual guanidinium thiocyanate (GuSCN) method. Real-time PCR results were compared with direct microscopy (Ziehl-Neelsen staining). The choice of GuSCN was justified by its chaotropic properties, which inactivate mycobacteria, stabilize RNA, and improve biosafety.
Results:
Among 48 samples, microscopy detected only nine (18.8%) positive cases, all from multibacillary (MB) patients. In contrast, real-time PCR detected 35 (72.9%) positives using the NucliSENS kit and 31 (64.6%) using the GuSCN method. In paucibacillary (PB) patients, PCR positivity reached 59.5%, whereas microscopy was nearly negative. Ear lobe exudates provided the best diagnostic yield.
Conclusion:
Real-time PCR targeting 16S rRNA significantly improves M. leprae detection compared to microscopy, especially in PB forms. The manual GuSCN method is a reliable, low-cost alternative for endemic settings. This approach can facilitate early case confirmation, subclinical infection detection, and support leprosy control efforts in Côte d'Ivoire within the WHO Zero Leprosy framework.
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